# LASTZ Release 1.04.52, built April 2, 2025

TABLE OF CONTENTS

- Introduction
- Availability
- Installation
- Build Options
- Overview of Processing Stages and Terminology
- Examples
  - Comparing a Human Chromosome and a Chicken Chromosome
  - Aligning Shotgun Reads to a Human Chromosome
  - Seeds, HSPs, Gapped Alignments, Chaining
  - Aligning a Sequence With Itself
- Command-line Syntax
  - Where to Look
  - Scoring
  - Indexing
  - Seeding
  - HSPs (Gap-free Extension)
  - Chaining
  - Gapped Extension
  - Back-end Filtering
  - Interpolation
  - Output
  - Housekeeping
  - Shortcuts for Yasra
  - Help
  - Sequence Specifiers
- Processing Stages in Detail
  - Target Sequence Input
  - Scoring Inference
  - Indexing Target Seed Words
  - Seeding
  - Gap-free Extension
  - HSP Chaining
  - Gapped Extension
  - Back-end Filtering
  - Interpolation
  - Alignment Output
- File Formats
  - FASTA
  - FASTQ
  - Nib
  - 2Bit
  - Quantum DNA
  - Quantum Code File
  - Sequence Name File
  - Sequence Masking File
  - Sequence Masking File, Three Fields
  - Scoring File
  - Inference Control File
  - HSX (Hashed Sequence Index)
  - Target Capsule File
  - Alignment Chores File
  - Segment File
  - LAV
  - AXT
  - MAF
  - SAM
  - CIGAR
  - BLASTN
  - PAF
  - PAF:wfmash
  - Differences
  - R Dotplot
  - Human-Readable Text
  - General Output
  - Other Output
- Advanced Topics
  - Aligning to Whole Genomes
  - Adjacent Indels
  - Interval Coordinates
  - Non-ACGT Characters, Splicing, and Separation
  - Sequence Name Mangling
  - Seed Patterns
  - Any-or-None Alignment
  - Y-drop Mismatch Shadow
  - Shingle Overlap
  - Using Target Capsule Files
  - Inferring Score Sets
  - Dynamic Programming Matrix
  - Filtering With Shell Commands
  - Self-Masking a Sequence
  - Aligning Many Subintervals
- Differences from BLASTZ
- Change History
  - Most Recent Changes
- References
- Acknowledgments

## Introduction

This document describes installation and usage of the LASTZ sequence alignment program. LASTZ is a drop-in replacement for BLASTZ, and is backward compatible with BLASTZ’s command-line syntax. That is, it supports all of BLASTZ’s options but also has additional ones, and may produce slightly different alignment results.

LASTZ: |  | A tool for (1) aligning two DNA sequences, and (2) inferring appropriate scoring parameters automatically.
Platform: |  | This package was developed on a Macintosh OS X system, but should work on other Unix or Linux platforms with little change (if any). LASTZ is written in C and compiled with gcc; other C compilers can probably be used by adjusting the Makefile. Some ancillary tools are written in Python, but only use modules available in typical python installations.
Author: |  | Bob Harris <rsharris at bx dot psu dot edu>
Date: |  | August 2021
Mailing list: |  | http://lists.bx.psu.edu/listinfo/lastz-users

## Availability

LASTZ is available from github at https://github.com/lastz/lastz.

A packed archive containing source code for LASTZ is available from the Miller Lab at Penn State. Note: 1.04.15 is the last release that will be available via the Miller Lab website.

## Installation

If you have received the distribution as a packed archive, unpack it by whatever means are appropriate for your computer. The result should be a directory `<somepath>/lastz‑distrib‑X.XX.XX` that contains a `src` subdirectory (and some others). You may find it convenient to remove the revision number (`‑X.XX.XX`) from the directory name.

Before building or installing any of the programs, you will need to tell the installer where to put the executable, either by setting the shell variable `$LASTZ_INSTALL`, or by editing the `make‑include.mak` file to set the definition of `installDir`. Also, be sure to add the directory you choose to your `$PATH`.

Then to build the LASTZ executable, enter the following commands from bash or a similar command-line shell (Solaris users should substitute `gmake` for `make`). This will build two executables (`lastz` and `lastz_D`) and copy them into your `installDir`.

        cd <somepath>/lastz-distrib-X.XX.XX/src
        make
        make install

The two executables are basically the same program; the only difference is that `lastz` uses integer scores, while `lastz_D` uses floating-point scores.

The build process should not report any warnings or errors. Because of this, the Makefile is set up so that warnings are considered errors and will stop the build. If you encounter this situation, you can use Makefile.warnings instead:

        make -f Makefile.warnings

This should allow the build to complete, while still reporting the warnings. You'll need to decide whether the warnings indicate something is really wrong. Usually they don't, but please report them to the author regardless.

A simple self test is included so you can test whether the build succeeded. To run it, enter the following command:

        make test

If the test is successful, you will see no output from this command. Otherwise, you will see the differences between the expected output and the output of your build, plus a line that looks like this:

        make: *** [test] Error 1

## Build Options

An additional executable (`lastz_32`) can be built, to handle genomes larger than 2 gigabases. For details, see the section on aligning to whole genomes.

An experimental executable (`lastz_40`) can be built, to handle genomes larger than 4 gigabases. For details, see the section on aligning to whole genomes.

Any executable can be built to allow adjacent indels (by default, these are not allowed). For details, see the section on adjacent indels.

## Overview of Processing Stages and Terminology

LASTZ is designed to preprocess one sequence or set of sequences (which we collectively call the target) and then align several query sequences to it. The general flow of the program is like a pipeline: the output of one stage is the input to the next. The user can choose to skip most stages via command-line options; any stages that are skipped pass their input along to the next stage unchanged. Two of the stages, scoring inference and interpolation, are special in that they perform a miniature version of the pipeline within them.

Note that the following discussion is a generalization, intended to describe the basic idea of LASTZ’s operation. There are many exceptions that depend on the particular options specified.

The stages are:

- read sequence(s) from target file
- infer scoring parameters (if necessary)
- build a seed word position table for the target
- for each sequence in query file:
  - find seeds
  - perform gap-free extension of seeds to HSPs
  - chain HSPs
  - perform gapped extension of HSPs to local alignments
  - filter alignments according to specified criteria
  - interpolate between alignments
  - print output
  - repeat with the reverse complement of the query

The usual flow is as follows (though most of these steps are optional, and some settings like `‑‑anyornone` may affect the processing order). We first read the target sequence(s) into memory, and use that to build a seed word position table that will allow us to quickly map any word in the target to all of the positions where it appears. (For the purposes of this discussion you can think of a word as a 12-mer of DNA.) Then we read each query sequence in turn, processing them more or less independently. We examine the word starting at each base in the query and use the position table to find matches, called seeds, in the target. The seeds are extended to longer matches called HSPs (high-scoring segment pairs) and filtered based on score. The HSPs are chained into the highest-scoring set of syntenic alignments, and then reduced to single locations called anchors. The anchors are then extended to local alignments (which may contain gaps) and again filtered by score, followed by back-end filtering to discard alignment blocks that do not meet specified criteria for certain traits. We then interpolate, repeating the entire process at a higher sensitivity in the holes between the alignment blocks. And finally, we write out the alignment information to a file. Then these steps are repeated with the reverse complement of the query sequence, before moving on to the next sequence in the query file.

The scoring inference stage is not usually performed. Typically it is used only when sequences for new species are acquired, to create scoring files for subsequent alignments of those species.

## Examples

For those eager to try it out, here are some illustrative examples to get you started. Detailed reference material begins with the next section.

### Comparing a Human Chromosome and a Chicken Chromosome

It is often adequate to use a lower sensitivity level than is achieved with LASTZ’s defaults. For example, to compare two complete chromosomes, even for species as distant as human and chicken, the alignment landscape is evident even at very low sensitivity settings. This can speed up the alignment process considerably.

This example compares human chromosome 4 to chicken chromosome 4. These sequences can be found in the downloads section of the UCSC Genome Browser, and are 191 and 94 megabases long, respectively. To run a quick low-sensitivity alignment of these sequences, use a command like this:

        lastz hg18.chr4.fa galGal3.chr4.fa \
          --notransition --step=20 --nogapped \
          --format=maf > hg18_4_vs_galGal3_4.maf

This runs in about two and a half minutes on a 2-GHz workstation, requiring only 400 Mb of RAM. Figure 1(a) shows the results, plotted using the `‑‑format=rdotplot` output option and the R statistical package. (When in MAF format, LASTZ output can be browsed with the GMAJ interactive viewer for multiple alignments, available from the Miller Lab at Penn State.)

Using `‑‑notransition` lowers seeding sensitivity and reduces runtime (by a factor of about 10 in this case). `‑‑step=20` also lowers seeding sensitivity, reducing runtime and also reducing memory consumption (by a factor of about 3.3 in this case). `‑‑nogapped` eliminates the computation of gapped alignments. The complete alignment process using default settings (shown in Figure 1(b)) uses 1.3 Gb of RAM and takes 4.5 hours on a machine running at 2.83 GHz.

Figure 1(a)

    lastz \
      hg18.chr4.fa galGal3.chr4.fa \
      --notransition --step=20 \
      --nogapped

Figure 1(b)

    lastz \
      hg18.chr4.fa galGal3.chr4.fa

### Aligning Shotgun Reads to a Human Chromosome

Short read mapping for close species requires parameters very different from LASTZ’s defaults. This example compares a simulated set of primate shotgun reads to human chromosome 21. The chromosome can be found in the downloads section of the UCSC Genome Browser (it is about 47 megabases). Ten thousand simulated reads were generated by extracting 60-bp intervals from chimp chr21, subjecting them to mild mutation (including short gaps), and then truncating them to 50 bp (these are included in the LASTZ distribution, in `test_data/fake_chimp_reads.2bit`).

To see where these reads map onto the human chromosome, use this command:

        lastz hg18.chr21.fa[unmask] fake_chimp_reads.2bit \
          --step=10 --seed=match12 --notransition --exact=20 --noytrim \
          --match=1,5 --ambiguous=n \
          --filter=coverage:90 --filter=identity:95 \
          --format=general:name1,start1,length1,name2,strand2 \
          > hg18_21_vs_reads.dat

Attaching `[unmask]` to the chromosome filename instructs LASTZ to ignore masking information and treat repeats the same as any other part of the chromosome, in order to accurately assess the uniqueness of the read mappings. Since we know the two species are close, we want to reduce sensitivity. Using `‑‑step=10`, we will only be looking for seeds at every 10th base. Instead of the default seed pattern, we use `‑‑seed=match12` and `‑‑notransition` so our seeds will be exact matches of 12 bases. Instead of the default `x-drop extension method` we use `‑‑exact=20` so that a 20-base exact match is required to qualify as an HSP. Because we are aligning short reads, we specify `‑‑noytrim` so the alignment ends will not be trimmed back to the highest scoring locations during gapped extension.

We replace the default score set, which is for more distant species, with the stricter `‑‑match=1,5`. This scores matching bases as +1 and mismatches as −5. We also use `‑‑ambiguous=n` so that `N`s will be scored appropriately. We are only interested in alignments that involve nearly an entire read, and since the species are close we don't want alignments with low identity; therefore we use `‑‑filter=coverage:90` and `‑‑filter=identity:95`.

For output, we are only interested in where the reads align, so we use the `‑‑format=general` option and specify that we want the position on the chromosome (`name1`, `start1`, `length1`) and the read name and orientation (`name2`, `strand2`). This creates a tab-delimited output file with one line per alignment block, a format that is well-suited for downstream processing by other programs. For example, to count the number of different reads we've mapped, we can run this Unix shell command:

        cat hg18_21_vs_reads.dat | grep -v "#" | awk '{print $4}' | sort -u | wc

### Seeds, HSPs, Gapped Alignments, Chaining

This example demonstrates the primary alignment processing stages, using the α-globin regions of cow and human. This data is included in the LASTZ distribution in `test_data/aglobin.2bit`, and consists of a 70K bp segment of human DNA and a 66K bp segment of cow DNA. We will follow this example through the major stages of seeding, gap-free extension, chaining, and gapped extension.

Figure 2(a) shows the result of default seeding on a small window (3K bp) in the middle of these segments. Seeds are short near-matches; in this case each seed is 19 bp and could have as many as 8 mismatches (12-of-19 with one transition). There are 338 seeds in this window, but regions where there are many seeds are indistinguishable from line segments.

Figure 2(b) shows high-scoring segment pairs, the result of gap-free extension of the seeds. There are 11 HSPs (only 10 are apparent in the figure, but one of those is split by a 1-bp shift to the next diagonal). Note that many seeds were discarded because their extensions were low scoring or overlapped.

Figure 2(c) shows the local alignment blocks resulting from gapped extension of the HSPs. There are four alignment blocks.

Then we zoom out and show the results for the full sequences; the red box indicates the small region shown in the earlier figures. Figure 2(d) shows the HSPs, 2(e) shows the gapped alignment blocks, and 2(f) illustrates how chaining reduces the alignment blocks to a single syntenic line (or two lines, if there were matches on both strands). Note that one can already tell quite a bit about how the sequences align just from looking at the HSPs.

Figure 2(a)

    lastz \
      aglobin.2bit/human[34000..37000] \
      aglobin.2bit/cow[35000..38000] \
      --nogfextend --nochain --nogapped

Figure 2(b)

    lastz \
      aglobin.2bit/human[34000..37000] \
      aglobin.2bit/cow[35000..38000] \
      --gfextend --nochain --nogapped

Figure 2(c)

    lastz \
      aglobin.2bit/human[34000..37000] \
      aglobin.2bit/cow[35000..38000] \
      --gfextend --nochain --gapped

Figure 2(d)

    lastz \
      aglobin.2bit/human \
      aglobin.2bit/cow \
      --gfextend --nochain --nogapped

Figure 2(e)

    lastz \
      aglobin.2bit/human \
      aglobin.2bit/cow \
      --gfextend --nochain --gapped

Figure 2(f)

    lastz \
      aglobin.2bit/human \
      aglobin.2bit/cow \
      --gfextend --chain --gapped

### Aligning a Sequence With Itself

When a sequence is aligned to itself, the full result will contain mirror-image copies of each alignment block. It is computationally wasteful to process both copies. LASTZ can handle this situation in four different ways.

1. Simply give LASTZ the same sequence for both the target and query. In this case, LASTZ does not know that it is aligning a sequence to itself, and performs the full computation on both copies (Figure 3(a)).

2. Specify the `‑‑notrivial` option. This performs the full computation on both copies, but doesn't report the trivial self-alignment block along the main diagonal (Figure 3(b)).

3. Specify the `‑‑self` option in place of the query sequence. LASTZ will save work by computing with only one block of each mirror-image pair, though it still reports both copies in the output by reconstructing the second copy from the first. It also invokes `‑‑notrivial` automatically to omit the trivial self-alignment block along the main diagonal. This gives the same output as the previous method, but runs faster (Figure 3(c)).

4. Specify `‑‑self` in place of the query, and also add the `‑‑nomirror` option. In this case LASTZ reports only one copy of each mirror-image pair, as well as omitting the trivial block (Figure 3(d)).

In the following figure, we suppose we have a sequence with repeated motifs, in the order α1 β1 γ1 β2 δ1 α2 δ2′ γ2. That is, α1 and α2 are ancient duplications, as are β1 and β2, and γ1 and γ2. δ2′ is an inversion, a reverse-complement duplicate of δ1.

Figure 3(a)

    lastz target target

Figure 3(b)

    lastz target target --notrivial

Figure 3(c)

    lastz target --self

Figure 3(d)

    lastz target --self --nomirror

## Command-line Syntax

If you are familiar with BLASTZ, you can run LASTZ the same way you ran BLASTZ, with the same options and input files. In addition to this BLASTZ compatibility, LASTZ provides other options.

The general format of the LASTZ command line is

        lastz <target> [<query>] [<options>]

The angle brackets `<>` indicate meta-syntactic variables that should be replaced with your values, while the square ones `[]` indicate elements that are optional. Spaces separate fields on the command line; a field that needs to contain a space (e.g. within a file name) must be enclosed in double quotes `""`. Elements can appear in any order, the only constraint being that, if present, the `<query>` must appear after the `<target>`. Output is generally written to `stdout`, unless specified otherwise for a particular option.

The `<target>` and `<query>` are usually just the names of files containing the sequences to be aligned, in either FASTA, Nib, or 2Bit format. However they can be HSX index files that refer to the sequences indirectly, and they also can specify pre-processing actions such as selecting a subsequence from the file (see Sequence Specifiers for details). With certain options such as `‑‑self` the `<query>` is not needed; otherwise if it is left unspecified the query sequences are read from `stdin` (though this does not work with random-access formats like 2Bit). As a special case, the `<target>` is omitted when the `‑‑targetcapsule` option is used, since the target sequence is embedded within the capsule file.

For options, the general format is `‑‑<keyword>` or `‑‑<keyword>=<value>`, but for BLASTZ compatibility some options also have an alternative syntax `<letter>=<number>`. (Be careful when copying options from the tables below, as some of the hyphens here are special characters to avoid awkward line wrapping in certain web browsers. If you have trouble, replace the pasted hyphens with ordinary typed ones on your command line.)

Please understand that LASTZ is a complex program and its options are not all independent, i.e., some options are not valid in combination with certain others. It would be difficult and cumbersome to attempt to list every possible conflict here; instead we just mention some of the major ones. If you are not sure about a particular combination, go ahead and try it — LASTZ will tell you if it’s not allowed.

Running the command `lastz` without any arguments prints a help message with the most commonly used options, while running

        lastz --help

lists all of the options.

### Where to Look

Option | BLASTZ equivalent | Meaning
`--strand=both` | `B=2` | Search both strands.
`--strand=plus` | `B=0` | Search the forward strand only (the one corresponding to the query specifier).
`--strand=minus` |  | Search only the reverse complement of the query specifier.

`--self`

Perform a self-alignment: the target sequence is also the query. Computation is more efficient than it would be without this option, since only one of each mirror-image pair of alignment blocks is processed (the other, redundant one is skipped during processing, but re-created in the output). Also, the trivial self-alignment block along the main diagonal is omitted from the output. This option cannot be used if the target is comprised of multiple sequences.

`--nomirror` |  | Inhibit the re-creation of mirror-image alignments. Output consists of only one copy of each meaningful alignment block in a self-alignment. This option is only applicable when the `‑‑self` option is used.
`--band=<width>` |  | Discard HSPs that are not within <width> above the main diagonal. This option is only allowed for self-alignment.
`--queryhsplimit=<n>` |  | Discard queries that have more than `<n>` HSPs. Any queries that exceed this limit are reported as a warning (to `stderr`), and no alignments are reported. This is useful for mapping reads to a reference genome, when some reads align to too many places in the reference.
`--queryhsplimit=nowarn:<n>` |  | Same as `‑‑queryhsplimit=<n>` but warnings for queries that exceed the limit are witheld.
`--queryhsplimit=keep,nowarn:<n>` |  | Same as `‑‑queryhsplimit=<n>` but queries that exceed the limit are not discarded and warnings are witheld. For such a query, the first `<n>` HSPs found are passed along to downstream processing. Note that the HSPs reported are not the best `<n>` HSPs. They are simply the first `<n>` found; they very likely have a positional bias.
`--queryhspbest=<n>` |  | For queries that have more than `<n>` HSPs, discard any HSPs that score below the `n`th best. This is useful for mapping reads to a reference genome, when some reads align to too many places in the reference.

`--querydepth=<n>`

Stop processing gapped alignments for a query/strand if its ratio of aligned bases to query length exceeds `<n>`. A warning is written to stderr, all alignments for the query/strand are discarded, and processing continues with the next query (or strand).

`‑‑querydepth=keep:<n>` can be used if the preference is to keep some alignments for such query/strands.

`<n>` is a real number and corresponds to a depth of coverage threshold. For example, a value of `5.0` would cause termination once a query/strand has an average of five alignments for every base in the query. The numerator is the number of matches or substitutions (but not gaps); the denominator is the length of the query sequence.

The purpose of this option is one of saving time. It is useful for automatically terminating the processing of queries with high repeat content, for which other methods of dealing with repetitive content fail.

Moreover, back-end filtering options are not considered. In other words, matches are counted for any alignment that meets the scoring threshold, regardless of whether that alignment would be reported. The justification is that we are trying to abort the processing of queries that have too many bounding alignments in the DP matrix, and back-end filtering occurs later in the process.

`--querydepth=keep:<n>`

Same as `‑‑querydepth=<n>` but any alignments discovered for this query/strand, before it exceeds the threshold, are reported.

Note that the alignments reported are not guaranteed to be the highest scoring alignments that would achieve the threshold. They are simply the first alignments found. In other words, the purpose of this option is one of saving time, not one of finding optimal alignments.

`--querydepth=nowarn:<n>` |  | Same as `‑‑querydepth=<n>` but warnings for queries that exceed the limit are witheld.
`--querydepth=keep,nowarn:<n>` |  | Same as `‑‑querydepth=<n>` but any alignments discovered for this query/strand, before it exceeds the threshold, are reported and warnings are witheld.
`--anyornone` |  | Stop processing after the first qualifying alignment has been found and written to the output, and move on to the next query. "Qualifying" means an alignment that meets all of the thresholds, etc. set by other options as usual. See Any-or-None Alignment for more details. This option is not compatible with chaining or interpolation.
Defaults: |  | By default both strands are searched, and the target is assumed to be different from the query. If `‑‑self` is used, the default is to re-create the redundant mirror-image alignment blocks in the output.

### Scoring

These are fundamental parameters for alignment scoring, used in several of the stages.

Option | BLASTZ equivalent | Meaning
`--scores=<scoring_file>` | `Q=<file>` | Read the substitution scores and gap penalties (and possibly other options) from a scoring file. This option cannot be used in conjunction with ‑‑match or inference.

`--match=<reward>[,<penalty>]`

Set the score values for a match (+`<reward>`) and mismatch (−`<penalty>`). These are both specified as positive values; the "+" and "−" are implicitly assumed. When `<penalty>` is not specified, it is the same as `<reward>`.

Note that specifying `‑‑match` changes the defaults for some of the other options (e.g. the scoring penalties for gaps, and various extension thresholds), as described in their respective sections. The regular defaults are chosen for compatibility with BLASTZ, but since BLASTZ doesn't support `‑‑match`, LASTZ infers that you are not expecting BLASTZ compatibility for this run, so it is free to use improved defaults.

This option cannot be used in conjunction with `‑‑scores` or `inference`.

`--gap=[<open>,]<extend>`

`O=<open>`
`E=<extend>`

Set the score penalties for opening and extending a gap. These are specified as positive values; subtraction is implicitly assumed. Note that the first base in a gap incurs the sum of both penalties.

This option is only valid if gapped extension is being performed, and cannot be used in conjunction with `inference`. These values specified on the command line override any corresponding values from a file provided with `‑‑scores`.

`--ambiguous=n[,<reward>][,<penalty>]`

Treat each `N` in the input sequences as an ambiguous nucleotide. Substitutions with `N` are scored as zero, instead of using the `fill_score` value from the scoring file (which is -100 by default).

A `<penalty>` can be specified, which will apply to any non-match substitution involving an `N`. If a `<reward>` is also specified, it applies to an N versus N match (otherwise, these matches are scored as zero). Note that the `<penalty>` is negated in the scoring matrix, while the `<reward>` is not.

See Non-ACGT Characters for a more thorough discussion. This option is not valid with quantum DNA.

Prior to version 1.02.20, this option was incorrectly implemented, and the fix has caused a change in behavior, and reported alignments, when `penalty` is not specified. See the change history item for details on how to maintain capatability with the earlier version, if that is desired.

`--ambiguous=iupac[,<reward>][,<penalty>]`

Treat each of the IUPAC-IUB ambiguity codes (`B, D, H, K, M, R, S, V, W,` and `Y`, as well as `N`) in the input sequences as a completely ambiguous nucleotide. Substitutions with these characters are scored as zero, instead of using the `fill_score` value from the scoring file (which is -100 by default).

A `<penalty>` can be specified, which will apply to any non-match substitution involving an ambiguous nucleotide. If a `<reward>` is also specified, it applies to a match involving ambiguous nucleotides (otherwise, these matches are scored as zero). Note that the `<penalty>` is negated in the scoring matrix, while the `<reward>` is not.

See Non-ACGT Characters for a more thorough discussion. This option is not valid with quantum DNA.

Note that this does not mean that LASTZ considers the specific ambiguity that is associated with each character (e.g. that `R` would be considered a match to an `A` or `G` but not to a `C` or `T`). Instead, they are all scored as if they were an `N`.

Prior to version 1.02.20, this option was incorrectly implemented, and the fix has caused a change in behavior, and reported alignments, when `penalty` is not specified. See the change history item for details on how to maintain capatability with the earlier version, if that is desired.

`--infer[=<control_file>]`

Infer substitution scores and/or gap penalties from the sequences, then use them to align the sequences. Parameters controlling the inference process are read from the control file. This feature is somewhat experimental, and special builds of LASTZ are required to enable it. Please see Inferring Score Sets for more information. Inference cannot be used in conjunction with `‑‑scores`, `‑‑match`, or `‑‑gap`.

`--inferonly[=<control_file>]` |  | Infer substitution scores and/or gap penalties, but don't perform the final alignment (requires `‑‑infscores`).
`--infscores[=<output_file>]` |  | Save the inferred scoring parameters to the specified file (or to `stdout`), in the same format expected by `‑‑scores`.

Defaults:

By default the HOXD70 substitution scores are used (see [Chiaromonte 2002] for an explanation of how this scoring matrix was determined).

| A | C | G | T
A | 91 | ‑114 | ‑31 | ‑123
C | ‑114 | 100 | ‑125 | ‑31
G | ‑31 | ‑125 | 100 | ‑114
T | ‑123 | ‑31 | ‑114 | 91

Default gap penalties are determined as follows. If `‑‑match` is specified, the open penalty is 3.25 times the mismatch penalty, and the extend penalty is 0.24375 times the mismatch penalty. (These are the same ratios as BLASTZ’s defaults.) Both penalties are rounded up to the nearest integer. Otherwise, the gap penalties are 400 for open, 30 for extend.

By default, a run of `N`s serves as an old-style separator between shotgun reads or other spliced sequences, rather than indicating ambiguous nucleotides. This is solely a consequence of the steep `fill_score` handicap imposed for substitutions with `N` — LASTZ doesn't normally search for runs of `N`s to treat specially (however, the `separator=N` action can be used to accomplish that, and is preferred if `N`s are intended to be separators).

### Indexing

Option | BLASTZ equivalent | Meaning
`--step=<offset>` | `Z=<offset>` | Offset between the starting positions of successive target words considered for potential seeds. (But this does not apply to the query words, which always use a step size of 1.)
`--maxwordcount=<limit>` |  | Words occurring more often than `<limit>` in the target are not eligible for seeds. Specifically, after the target seed word position table is built, any words exceeding this count are removed from the table.

`--maxwordcount=<limit>%`

Set `maxwordcount` to keep a specified percentage of seed word positions. `<limit>` is a lower bound on the percentage of words to be kept (0 < `limit` < 100).

Setting this as a percentage makes it easier to maintain consistency across runs. The actual count is dependent on sequence length and composition as well as the step offset and seed pattern. For example, Figure 4 shows the variation among human chromosomes in hg18 for `‑‑seed=match13`, `‑‑step=15`, and `‑‑maxwordcount=90%`. The gray bars show the percentage of seed word positions kept (the red line shows the ideal 90%). The blue numbers show the equivalent count, which varies greatly.

Figure 4

`--masking=<count>`

`M=<count>`

Dynamically mask the target sequence by excluding any positions that appear in too many alignments from further consideration for seeds.

Specifically, a cumulative count is maintained of the number of times each target location is aligned. After each query sequence and strand is processed, any locations that have been output in at least `<count>` alignment blocks are masked, so they will be excluded from the seeding stage for subsequent query sequences. Since repetition discovered while processing one sequence strand is only masked for subsequent sequence strands, this option has no effect on the first strand of the first sequence in the query file.

This option requires one, two, or four bytes of memory for each target location, depending on `<count>`. If `<count>` is 254 or less, one byte is used; if it is 65,534 or less, two bytes are used.

The resulting masked intervals can be written to a file with the `‑‑outputmasking=<file>` option.

`--targetcapsule=<capsule_file>` |  | The target seed word position table and seed (as well as the target sequence) are read from the specified file. When this option is used, the normal target specifier is omitted from the command line, and the following options are not allowed: `‑‑step`, `‑‑maxwordcount`, `‑‑masking`, `‑‑seed`, `‑‑word`.
`--chores=<chores_file>` |  | Restrict alignment to a list of subintervals. The file describes a list of sequence interval pairs, indicating that the alignment process is to be restricted to those intervals. See Aligning Many Subintervals for advice on when to use this option.
`--segments=<segment_file>` |  | Read anchor segments from a file, instead of discovering them via seeding. This replaces any other options related to indexing, seeding, gap-free extension or chaining. Those stages are skipped, and processing begins with the gapped extension stage. See Aligning Many Subintervals for advice on when to use this option.
Defaults: |  | By default a step of 1 is used, no words are removed from the target seed word position table, dynamic masking is not performed, and no target capsule or segment file is used.

### Seeding

Option | BLASTZ equivalent | Meaning
`--seed=12of19` | `T=1` or `T=2` | Seeds require a 19-bp word with matches in 12 specific positions (`1110100110010101111`).
`--seed=14of22` | `T=3` or `T=4` | Seeds require a 22-bp word with matches in 14 specific positions (`1110101100110010101111`).
`--seed=match<length>` | `W=<length>` | Seeds require a `<length>`-bp word with matches in all positions.
`--seed=half<length>` |  | Seeds require a `<length>`-bp word with matches or transitions in all positions. This option is not valid with quantum DNA.
`--seed=<pattern>` |  | Specifies an arbitrary pattern of `1`s, `0`s, and `T`s for seed discovery. (Note that `T`s are not valid with quantum DNA.)
`--transition` | `T=1` or `T=3` | In each seed, allow any one match position to be a transition instead. This option is not valid with quantum DNA.
`--transition=2` |  | In each seed, allow any two match positions to be transitions instead. This option is not valid with quantum DNA.
`--notransition` | `T=2` or `T=4` | Don't allow any match positions in seeds to be satisfied by transitions.
`--filter=[<transv>,]<matches>` |  | Filter the resulting seeds, requiring at least `<matches>` exact matches and allowing no more than `<transv>` transversions. If `<transv>` is not specified, any number of transversions is allowed (they are not limited). This option is not valid with quantum DNA.
`--nofilter` |  | Don't filter seeds.
`--ball=<score>` |  | Set the quantum seeding threshold, the minimum score required of a DNA word to be included in the seeding ball.
`--ball=<percentage>%` |  | Set the quantum seeding threshold as a percentage of the maximum word score possible.
`--twins=[<minsep>..]<maxsep>` |  | Require two nearby seeds on the same diagonal, separated by a number of bases in the given range. See the Seed Patterns section for more information. This option cannot be used in conjunction with `‑‑recoverseeds`.
`--notwins` |  | Allow single, isolated seeds.
`--recoverseeds` |  | Avoid losing seeds in hash collisions. This will slow the alignment process considerably and cost more memory, and usually does not improve the results significantly. See the Gap-free Extension stage for more information. This option cannot be used in conjunction with `‑‑twins`.
`--norecoverseeds` |  | Ignore hash collisions, at the expense of missing some seeds. Note that missing seeds usually does not mean missing alignments, since most alignable regions have many seed hits.
Defaults: |  | By default the 12-of-19 seed is used, one transition is allowed (except with quantum DNA), the hits are not filtered, twins are not required, and hash collisions are not recovered. If the `quantum` action is used in the query file’s sequence specifier, the default ball scoring threshold is 75% of the maximum word score possible.

### Finding HSPs (Gap-free Extension)

Option | BLASTZ equivalent | Meaning
`--gfextend` |  | Perform gap-free extension of seeds to HSPs (high scoring segment pairs), according to the other options in this section.
`--nogfextend` |  | Skip the gap-free extension stage, passing the seeds along to the next specified stage. It is not recommended to use `--nogfextend` without also using `--nogapped`.
`--exact=<length>` |  | Find HSPs using the exact match extension method with the given length threshold, instead of using the x-drop method.
`--mismatch=<count>,<length>` |  | Find HSPs using the mismatch extension method with the given length threshold and allowing `count` mismatches, instead of using the x-drop method. `count` is limited to the range `1≤count≤50`.

`--xdrop=<dropoff>`

`X=<dropoff>`

Find HSPs using the x-drop extension method with the given termination threshold, instead of using the exact match method. The dropoff setting determines the endpoints of each gap-free segment: the extension of each seed is stopped when its cumulative score drops off by more than the given threshold from the maximum seen so far. See the Gap-free Extension stage for more details.

`--hspthresh=<score>` | `K=<score>` | Set the score threshold for the x-drop extension method; HSPs scoring lower are discarded.
`--hspthresh=top<basecount>` |  | Set an adaptive score threshold for the x-drop extension method; HSPs scoring lower are discarded. The score threshold is chosen to limit the number of target sequence bases in HSPs to about `<basecount>` (or possibly a little higher in case of ties, etc.).
`--hspthresh=top<percentage>%` |  | Set an adaptive score threshold for the x-drop extension method; HSPs scoring lower are discarded. The score threshold is chosen to limit the number of target sequence bases in HSPs to about `<percentage>` percent of the target (or possibly a little higher in case of ties, etc.).
`--entropy` | `P=1` | Adjust for entropy when qualifying HSPs in the x-drop extension method. Those that score just slightly above the HSP threshold are adjusted downward according to the entropy of their nucleotides, and any that then fall below the threshold are discarded.
`--entropy=report` | `P=2` | Adjust for entropy when qualifying HSPs in the x-drop extension method, and report (to `stderr`) any HSPs that are discarded as a result.
`--noentropy` | `P=0` | Don't adjust for entropy when qualifying HSPs.

Defaults:

By default seeds are extended to HSPs using x-drop extension, with entropy adjustment.

If `‑‑match` scoring is used, the default x-drop termination threshold is 10 times the square root of the mismatch penalty, rounded up to the nearest integer. Otherwise the default is 10 times the A-vs.-A substitution score.

If `‑‑match` scoring is used, the default HSP score threshold is 30 times the match reward (equivalent to the score of a 30-bp exact match). Otherwise the default is 3000.

`‑‑help=defaults` can be used to see what values are set.

### Chaining

Option | BLASTZ equivalent | Meaning
`--chain` | `C=1` or `C=2` | Perform chaining of HSPs with no penalties.
`--chain=<diag>,<anti>` | `C=1` or `C=2` `G=<diag>` `R=<anti>` | Perform chaining with the given penalties for diagonal and anti-diagonal in the DP matrix. These are specified as positive values; subtraction from the score is implicitly assumed.
`--nochain` | `C=0` or `C=3` | Skip the chaining stage.
Defaults: |  | By default the chaining stage is skipped.

### Gapped Extension

Option | BLASTZ equivalent | Meaning
`--gapped` | `C=0` or `C=2` | Perform gapped extension of HSPs (or seeds, if gap-free extension is not performed), after first reducing them to anchor points.
`--nogapped` | `C=1` or `C=3` | Skip the gapped extension stage. (This means that interpolation must also be skipped, since it is not allowed without gapped extension.)

`--ydrop=<dropoff>`

`Y=<dropoff>`

Set the threshold for terminating gapped extension; this restricts the endpoints of each local alignment by limiting the local region around each anchor in which extension is performed. The boundary of this region in the DP matrix is formed by the points where the cumulative score has dropped off by more than the given threshold from the maximum seen so far. See the Gapped Extension stage for more details.

`--noytrim` |  | If y-drop extension encounters the end of the sequence, extend the alignment to the end of the sequence rather than trimming it back to the location giving the maximum score. This is highly recommended when either the target or query sequences are short reads (say, less than 100 bases), to prevent y-drop mismatch shadow.

`--gappedthresh=<score>`

`L=<score>`

Set the threshold for gapped extension; alignments scoring lower than `<score>` are discarded. When used along with the x-drop method for gap-free extension, this value is generally set at least as high as the HSP threshold. Setting it lower has no effect, since at worst the HSP itself would always qualify (both extension stages use the same scoring matrix).

`--allgappedbounds` |  | Revert to handling bounding alignments the way they were handled in BLASTZ. This is discussed in Bounding Alignments in the DP Matrix.

Defaults:

By default gapped extension is performed, and alignment ends are trimmed to the locations giving the maximum score.

If `‑‑match` scoring is used, the default y-drop threshold is twice the x-drop threshold (or if x-drop extension was not performed, twice what the default x-drop threshold would have been); otherwise it is the score of a 300-bp gap.

The default for the gapped score threshold is to use the same value as the HSP threshold (which is settable via `‑‑hspthresh`). If the HSP threshold was adaptive, then the lowest-scoring HSP that was kept is used for this default. If x-drop extension was not performed, the value used is whatever the default HSP threshold would have been.

`‑‑help=defaults` can be used to see what values are set.

### Back-end Filtering

Option | BLASTZ equivalent | Meaning
`--filter=identity:<min>[..<max>]` |  | Filter alignments by their percent identity, 0 ≤ `min` ≤ `max` ≤ 100 percent. Identity is the percentage of aligned bases that are matches. Alignment blocks outside the given range are discarded. This option is not valid with quantum DNA. For backwards compatibility, `‑‑identity=<min>[..<max>]` has the same meaning.
`--filter=continuity:<min>[..<max>]` |  | Filter alignments by how much of the input sequence aligns as matches or mismatches, rather than gaps, 0 ≤ `min` ≤ `max` ≤ 100 percent. Continuity is the percentage of alignment columns that are not gaps. Alignment blocks outside the given range are discarded. For backwards compatibility, `‑‑continuity=<min>[..<max>]` has the same meaning.
`--filter=coverage:<min>[..<max>]` |  | Filter alignments by how much of the input sequence they cover, 0 ≤ `min` ≤ `max` ≤ 100 percent. Coverage is the percentage of the entire target or query sequence (whichever is shorter) that is included in the alignment block. Blocks outside the given range are discarded. For backwards compatibility, `‑‑coverage=<min>[..<max>]` has the same meaning.
`--filter=nmatch:<min>` |  | Filter alignments by how many bases match, requiring at least `min` matched bases, `min` > 0. Match count, or `nmatch`, is the number of matched bases in the alignment. This option is not valid with quantum DNA. For backwards compatibility, `‑‑matchcount=<min>` has the same meaning.
`--filter=nmatch:<min>%` |  | Filter alignments by how many bases match, with the threshold specified as a percentage of the query length.
`--filter=nmismatch:0..<max>` |  | Filter alignments by the number of mismatches, allowing no more than `max` mismatched bases, `max` ≥ 0. Mismatch count, or `nmismatch`, is the number of aligned bases in the alignment that are mismatches (substitutions). This option is not valid with quantum DNA.
`--filter=ngap:0..<max>` |  | Filter alignments by the number of gaps, allowing no more than `max` gaps, `max` ≥ 0. Gap count, or `ngap`, is the number of runs of gapped columns in the alignment (each run is counted as one gap).
`--filter=cgap:0..<max>` |  | Filter alignments by the number of gap columns, allowing no more than `max` gaps, `max` ≥ 0. Gap column count, or `cgap`, is the number of gapped columns in the alignment (each column is counted as one gap).
`--notrivial` |  | Do not output a trivial self-alignment block if the target and query sequences are identical. Note that using `‑‑self` automatically enables this option.
Defaults: |  | By default no back-end filtering is performed, and the trivial block is included if the sequences happen to be identical.

### Interpolation

Option | BLASTZ equivalent | Meaning
`--inner=<score>` | `H=<score>` | Perform additional alignment between the gapped alignment blocks, using (presumably) more sensitive alignment parameters. `<score>` is used as the threshold for both the gap-free and gapped extension sub-stages; see the discussion of interpolation for more details. This option is only valid if gapped extension is performed.
Defaults: |  | By default interpolation is not performed.

### Output

Option | BLASTZ equivalent | Meaning
`--output=<output_file>` |  | Write the alignments to the specified file name instead of `stdout`.
`--format=<type>` |  | Specifies the output format: `lav`, `lav+text`, `axt`, `axt+`, `maf`, `maf+`, `maf-`, `sam`, `softsam`, `sam-`, `softsam-`, `sam+eqx`, `softsam+eqx`, `sam+eqx-`, `softsam+eqx-`, `cigar`, `BLASTN`, `PAF`, `PAF:wfmash`, `differences`, `rdotplot`, `text`, `general[:<fields>]`, or `general-[:<fields>]`. `‑‑format=none` can be used when no alignment output is desired.
`--axt=<file>` |  | Create an additional output file in AXT format. The output file is the same as would be produced by `‑‑format=axt`, but this option allows you to create the axt file while also outputting in any other format, without having to run the alignment twice.
`--maf=<file>` |  | Create an additional output file in MAF format. The output file is the same as would be produced by `‑‑format=maf`, but this option allows you to create the maf file while also outputting in any other format, without having to run the alignment twice.
`--rdotplot=<file>` |  | Create an additional output file suitable for plotting the alignment blocks with the R statistical package. The output file is the same as would be produced by `‑‑format=rdotplot`, but this option allows you to create the dotplot file without having to run the alignment twice.

`--readgroup=<tags>`

Used in conjuction with the SAM file format, allowing the specification of tags for SAM's `‑RG` header line. `<tags>` is a tab-delimited list of `<tag>:<value>` items. See the SAM specification for details about which tags are required. LASTZ does not validate whether the list is a valid SAM tag list.

Since the list is tab-delimited, you may need to surround this option with quotes to satisfy the command line shell. Alternately, you can use `--readgroup` more than once, and the lists are concatenated.

`--eqx` |  | Used in conjuction with the SAM file format, indicating that the operators "=" and "X" should be used in CIGAR strings, instead of the ambiguous "M" operator. This option is included for users familiar with minimap2. Equivalently, the string "+eqx" can be attached to the SAM format option.

`--markend`

Just before normal completion, write a marker line

        # lastz end-of-file

to the output file. This option can be useful with pipelines or batch servers, where there may be a question as to whether or not LASTZ completed successfully. Note that in some output formats this marker is not a legal line, in which case you must remove it before any downstream processing.

`--census[=<output_file>]`

`c=1`

Count and report how many times each target base aligns, up to 255. `N`s are included in the count (both bases that are `N`s and bases aligning to `N`s), and even bases aligning to gaps are counted. Requires one byte of memory for each target location.

For any of the `lav` formats, if `<output_file>` is omitted the census is included as a special stanza in the output. For all other formats `<output_file>` is mandatory.

`--census16[=<output_file>]` |  | Count and report how many times each target base aligns, up to ≈65 thousand. Requires two bytes of memory for each target location.
`--census32[=<output_file>]` |  | Count and report how many times each target base aligns, up to ≈4 billion. Requires four bytes of memory for each target location.
`--nocensus` | `c=0` | Do not report a census of aligning bases.

`--outputmasking=<file>`

Used in conjuction with the `‑‑masking=<count>` option. The masked target intervals, resulting from alignment with all queries, are written to a file in sequence masking file format. The file is suitable for later use with the `softmask`, `xmask`, and `nmask` sequence specifier actions.

In contrast with `‑‑outputmasking:soft=<file>`, only those intervals created by the `‑‑masking=<count>` option are reported.

`--outputmasking+=<file>` |  | The same as `‑‑outputmasking=<file>`, except that masked intervals are written to a file in three field sequence masking file format, which includes sequence names. The file is not suitable for later use as input to LASTZ. This is useful when the target file contains more than one sequence.

`--outputmasking:soft=<file>`

Soft-masked target intervals (lowercase bases) are written to a file in sequence masking file format. The file is suitable for later use with the `softmask`, `xmask`, and `nmask` sequence specifier actions.

In contrast with `‑‑outputmasking=<file>`, all masked intervals in the target sequence are reported, regardless of whether they were created by the `‑‑masking=<count>` option or were in the sequence as it was originally input.

`--outputmasking+:soft=<file>` |  | The same as `‑‑outputmasking:soft=<file>`, except that masked intervals are written to a file in three field sequence masking file format, which includes sequence names. The file is not suitable for later use as input to LASTZ. This is useful when the target file contains more than one sequence.
`--tableonly` |  | Just write out the target seed word position table and quit; don't search for seeds or perform any subsequent stages.
`--tableonly=count` |  | Just write out the target word count table and quit; don't search for seeds or perform any subsequent stages.
`--writecapsule=<capsule_file>` |  | Just write out a target capsule file and quit; don't search for seeds or perform any subsequent stages. The capsule file contains the target sequence, the seed, the target seed word position table, and other related information.

`--writesegments=<segment_file>`

Write out alignments as segments, in the same format used for input by the `‑‑segments` option. These anchor segments can then be used to anchor alignments in a subsequent run of LASTZ. This can be useful if you want to filter HSPs in some way before performing gapped extension, for example filtering them by length. Since anchor segments must be gap-free, this option cannot be used in conjunction with gapped extension.

`--progress[=<N>]` | `` | Report the count and name of every `N`th query to stderr, as processing begins on that query. If N is omitted, every query is reported.
`--progress+masking[=<N>]` | `` | Report the count and name of every `N`th query to stderr, with statistics relating to dynamic masking, as processing begins on that query. If N is omitted, every query is reported.
`--progress:hspsearch=<N>` | `` | Report progress of the HSP search stage as every `N`th HSP is discovered. Each report shows the position of the search along the sequence, as well as the percentage of the sequence that has been completed. This can be useful to estimate how long the HSP search stage will take.

`--progress:filter=<N>`

``

Report progress of back-end filtering during the HSP search stage as every `N`th HSP is subjected to the filters. Each report shows the numbers of HSPs that have passed or been rejected by the filter. The position of the search along the sequence is also shown, as well as the percentage of the sequence that has been completed.

Note that filters are only applied to HSPs if the gapped stage will be skipped (otherwise, they are applied to the gapped alignments).

This can be useful to understand the efficacy of the filter settings.

`--progress:segments=<N>` | `` | Report progress of the gapped alignment stage as every `N`th segment (a.k.a. anchor) is processed. Each report shows the number of the segment being processed, as well as the percentage of the segments that have been completed. This can be useful to estimate how long the gapped alignment stage will take.
`--show=defaults` | `` | List the option values lastz is using. This can be helpful if you are unsure what the default value is for most common settings. This gives the same information as `‑‑help=defaults`, but writes them to the output file. For some formats, this renders the output file as non-conformant.
Defaults: |  | By default alignments are written to `stdout` in `lav` format, no census is reported, and no target table or capsule is written out.

### Housekeeping

Option | BLASTZ equivalent | Meaning

`--include=<file>`

Read arguments from a text file. The arguments are parsed the same as they would be from the command-line, with the exception that they may appear on multiple lines in the file. `‑‑include` can be used in conjunction with other command line arguments.

Note that any shell-performed substitutions that would be performed on the command line are not performed on the contents of the text file.

`--allocate:traceback=<bytes>`

`m=<bytes>`

Set the amount of memory to allocate (in RAM) for trace-back information during the gapped extension stage. `<bytes>` may contain an `M` or `K` unit suffix if desired (indicating a multiplier of 1,024 or 1,048,576, respectively). For example, `‑‑allocate:traceback=80.0M` is the same as `‑‑allocate:traceback=83886080`.

This is limited to a maximum of 2G.

For backwards compatibility, `‑‑traceback=<bytes>` is also accepted.

`--allocate:target=<bytes>`

Predict the amount of memory (in RAM) that will be needed for target sequence data. Normally LASTZ incrementally predicts the amount of memory needed as it parses the file. In some instances that incremental allocation can lead to memory overuse (depending on details of how the operating system handles memory allocation). Predicting the memory needed prevents that.

The memory needed for a sequence is `L+1`, where `L` is the length of the sequence. When `multiple` is used, the total memory needed is the sum of that needed for each sequence.

`--allocate:query=<bytes>` |  | Predict the amount of memory (in RAM) that will be needed for query sequence data. See `‑‑allocate:target` for further details. The memory needed for a sequence is `L+1`, where `L` is the length of the sequence. When the query file contains more than one sequence and `multiple` is not used, the memory needed is that needed for the longest sequence.
`--action:target=<action>` |  | Set a sequence specifier action for the target. This is an alternative to appending the action to the target filename, and is useful for shells that make using square brackets problematic. This can be used more than once in the command line, the actions are all applied.
`--action:query=<action>` |  | Set a sequence specifier action for the query. This is an alternative to appending the action to the target filename, and is useful for shells that make using square brackets problematic. This can be used more than once in the command line, the actions are all applied.
`--word=<bits>` |  | Set the maximum number of bits for the word hash. Use this to spend less memory (in exchange for more time) and thereby avoid thrashing for heavy seeds.
Defaults: |  | The default traceback space is `80.0M`, target and query memory is allocated as needed, and the default word hash is 28 bits.

### Shortcuts for Yasra

There are several shortcut options to support the Yasra mapping assembler. These provide canned sets of option settings that work well for aligning an assembled reference sequence (as the target) with a set of shotgun reads (as the query). They are selected based on the expected level of identity between the sequences. For example, `‑‑yasra90` should be used when we expect 90% identity. The `‑‑yasraXXshort` options are appropriate when the reads are very short (less than 50 bp).

Option | Equivalent
`--yasra98` | `T=2 Z=20 ‑‑match=1,6 O=8 E=1 Y=20 K=22 L=30 ‑‑filter=identity:98 ‑‑ambiguous=n ‑‑noytrim`
`--yasra95` | `T=2 Z=20 ‑‑match=1,5 O=8 E=1 Y=20 K=22 L=30 ‑‑filter=identity:95 ‑‑ambiguous=n ‑‑noytrim`
`--yasra90` | `T=2 Z=20 ‑‑match=1,5 O=6 E=1 Y=20 K=22 L=30 ‑‑filter=identity:90 ‑‑ambiguous=n ‑‑noytrim`
`--yasra85` | `T=2 ‑‑match=1,2O=4 E=1 Y=20 K=22 L=30 ‑‑filter=identity:85 ‑‑ambiguous=n ‑‑noytrim`
`--yasra75` | `T=2 ‑‑match=1,1O=3 E=1 Y=20 K=22 L=30 ‑‑filter=identity:75 ‑‑ambiguous=n ‑‑noytrim`
`--yasra95short` | `T=2 ‑‑match=1,7O=6 E=1 Y=14 K=10 L=14 ‑‑filter=identity:95 ‑‑ambiguous=n ‑‑noytrim`
`--yasra85short` | `T=2 ‑‑match=1,3O=4 E=1 Y=14 K=11 L=14 ‑‑filter=identity:85 ‑‑ambiguous=n ‑‑noytrim`

Occasionally, newer releases of LASTZ change the Yasra shortcut options. This is done as an improvement, so most users will want to use the shortcuts shown above. Hoever, in order to support backward compatibility for users that want to reproduce previous results, all previous versions of the shortcuts are included. The syntax is `‑‑<shortcut>:<version>`, where `<version>` is the LASTZ version number that contained the shortcut.

Option | LASTZ version | Equivalent
`--yasra98:<version>` | 1.02.45 or earlier | `T=2 Z=20 ‑‑match=1,6 O=8 E=1 Y=20 K=22 L=30 ‑‑filter=identity:98`
`--yasra95:<version>` | 1.02.45 or earlier | `T=2 Z=20 ‑‑match=1,5 O=8 E=1 Y=20 K=22 L=30 ‑‑filter=identity:95`
`--yasra90:<version>` | 1.02.45 or earlier | `T=2 Z=20 ‑‑match=1,5 O=6 E=1 Y=20 K=22 L=30 ‑‑filter=identity:90`
`--yasra85:<version>` | 1.02.45 or earlier | `T=2 ‑‑match=1,2O=4 E=1 Y=20 K=22 L=30 ‑‑filter=identity:85`
`--yasra75:<version>` | 1.02.45 or earlier | `T=2 ‑‑match=1,1O=3 E=1 Y=20 K=22 L=30 ‑‑filter=identity:75`
`--yasra95short:<version>` | 1.02.45 or earlier | `T=2 ‑‑match=1,7O=6 E=1 Y=14 K=10 L=14 ‑‑filter=identity:95`
`--yasra85short:<version>` | 1.02.45 or earlier | `T=2 ‑‑match=1,3O=4 E=1 Y=14 K=11 L=14 ‑‑filter=identity:85`

### Help

Option | Meaning
`--version` | Report the program version and quit.
`--help` | List all options.
`--help=defaults` | List the option values lastz would use given the rest of the command line. This can be helpful if you are unsure what the default value is for most common settings. This gives the same information as `‑‑show=defaults`.
`--help=files` | Describe the syntax for sequence specifiers.
`--help=formats` | Describe the available output formats.
`--help=shortcuts` | List BLASTZ-compatible shortcuts.
`--help=yasra` | List Yasra-specific shortcuts.

### Sequence Specifiers

A target or query sequence specifier normally just indicates a file to be used in the alignment; however various pre-processing actions can also be specified. These are performed as the sequences are read from the file, and may include selecting a particular sequence and/or subrange, masking, adjusting sequence names, etc.

The format of a sequence specifier is

        <file_name>[[<actions>]]*

The `<file_name>` field is required; the actions list is optional. Note that the `<actions>` are enclosed in literal square brackets (in addition to the meta ones that just indicate they are optional), and consist of a comma-separated list (with no spaces), e.g. `[action1,action2,...]`. The `*` indicates that several action lists can be appended; they are treated the same as if they were in a single list.

Alternatively, actions can be specified with the commands `‑‑action:target=<action>` and `‑‑action:query=<action>`. This allows actions to be set without using square brackets (square brackets are problematic in some command shells).

Note that the actions apply to every sequence in the file. For example, if you specify a subrange of, say, `[100..]`, you will skip the first 99 bp in every sequence.

The following actions are supported:

Action | Meaning

`<subrange>`

Only a subrange of the sequence is processed. The usual form of a subrange is `[<start>]..[<end>]`. Either `<start>` or `<end>` can be omitted, in which case the start or end of the sequence is used. Subrange indices begin with 1 and are inclusive (i.e., they use the origin-one, closed position numbering system). For example, `201..300` is a 100-bp subrange that skips the first 200 bp in the sequence.

For BLASTZ compatibility, the alternative syntax `<start>,<end>` is also recognized. In this case both `<start>` and `<end>` are required.

A “zoom out factor” can also be included, using the syntax `<start>..<end>+<zoom>%`. The specified interval is expanded on each end by `<zoom>` percent. This is useful when you know, for example, the location of a gene, and would like to include flanking regions in the alignment.

Another useful syntax for this is `<start>#<length>`, which is handy for specifying an interval of known length at a given position; it is equivalent to `<start>..<start+length−1>`. Similarly, `<center>^<length>` specifies an interval of known length centered at the given position. Large lengths can be specified using `M` or `K` units if desired, e.g. `10.2M`.

Additionally, if a subrange has `<start>` larger than `<end>`, the reverse complement of the extracted region is used. However, this can lead to non-obvious interactions with other features such as strand reporting, sequence masking, and segment files, so it should be used with care. Usually it is simpler to use the `‑‑strand` options instead.

Note that subrange positions are always measured from the start of the sequence provided in the file (i.e., counting along the forward strand), even if the sequence is being reverse complemented.

`multiple` | The file’s sequences are internally treated as a single sequence. This action is required when the target (not the query) is comprised of multiple sequences. There is rarely any reason to use the `multiple` action for the query file. Doing so can negatively affect memory use and run time.

`separator=<character>`

The file’s sequences are internally broken in pieces wherever the specified `<character>` occurs, so that alignments will not cross that separator. The separation action is performed after any masking action (such as `xmask` or `nmask`), so it is possible to use the masking operation to mark the sequence with separators.

The character can be any printable ASCII character. However, characters that are important in the input format being used (for example a “>” in fasta) should not be used for this purpose. Moreover, many input formats have limited capability to represent characters other than nucleotides. There is no error checking regarding the specified `<character>` — if that character does not occur at all in the input, no separation is performed.

See Non-ACGT Characters, Splicing, and Separation for further details.

`subset=<names_file>` | Process only a specified subset of the sequences in the file. `<names_file>` is the name of a file containing a list of desired sequence names; only these sequences will be processed. The names can be piped in by specifying `/dev/stdin` as the file. This action is only valid for FASTA, 2Bit, or HSX input files.
`subsample=<k>/<n>` | Process only the `k`th sequence of every group of `n` sequences. `k` ranges from 1 to `n`. This action is only valid for FASTA, 2Bit, or HSX input files.
`chores=<chores_file>` | Restrict alignment to a list of subintervals. This is equivalent to the the `‑‑chores=<chores_file>` option.
`unmask` | Convert any lowercase bases to uppercase. Lowercase bases usually indicate instances of biological repeats, and are excluded from the seeding stage of the alignment process.
`softmask=<mask_file>` | Mask the segments specified in `<mask_file>` by replacing them with lowercase equivalents. Lowercase bases usually represent instances of biological repeats, and are excluded from the seeding stage of the alignment process but not from later stages. Note that soft masking is performed after any unmasking.
`softmask=keep:<mask_file>` | Mask the segments not specified in `<mask_file>` by replacing them with lowercase equivalents. Any base not in one of the specified intervals is replaced, and thereby excluded from the seeding stage (but not later stages) of the alignment process.
`xmask=<mask_file>` | Mask the segments specified in `<mask_file>` by replacing them with `X`s. (Note that this always masks with actual `X`s, even if the scoring file specifies a different character as "bad".) See Non-ACGT Characters, Splicing, and Separation for information on how `X`s affect the alignment process.
`xmask=keep:<mask_file>` | Mask the segments not specified in `<mask_file>` by replacing them with `X`s. Any base not in one of the specified intervals is replaced.
`nmask=<mask_file>` | Mask the segments specified in `<mask_file>` by replacing them with `N`s. See Non-ACGT Characters, Splicing, and Separation for information on how `N`s affect the alignment process.
`nmask=keep:<mask_file>` | Mask the segments not specified in `<mask_file>` by replacing them with `N`s. Any base not in one of the specified intervals is replaced.
`nameparse=full` | Report full sequence names in the output, instead of short names. As described in Sequence Name Mangling, LASTZ normally shortens FASTA and 2Bit sequence names in an attempt to include only the distinguishing core of the name. This action is provided in case LASTZ’s choice of names is not helpful. It is only valid for FASTA or 2Bit sequence files.
`nameparse=darkspace` | Extract the first word from the sequence header line, keeping only a non-whitespace string. If the first word is a filename, any directory/folder information is discarded. See Sequence Name Mangling for more information on how the name used for output is derived. This action is currently only valid for FASTA or 2Bit sequence files.

`nameparse=alphanum`

Extract the first word from the sequence header line, keeping only an alphanumeric string. If the first word is a filename, any directory/folder information is discarded; then the name is truncated at the first character that is not a letter, digit, or underscore. See Sequence Name Mangling for more information on how the name used for output is derived. This action is currently only valid for FASTA or 2Bit sequence files.

`nameparse=tag:<marker>`

Use the specified marker to extract a short name from the sequence header line. For example, `nameparse=tag:foo` will look for the string `foo` in the header line, and copy the name from the text following that, up to the next non-alphanumeric character. See Sequence Name Mangling for more information on how the name used for output is derived. This action is only valid for FASTA or 2Bit sequence files.

`nickname=<name>` | Ignore any sequence names in the input file, instead using `<name>` in the output. See Sequence Name Mangling for more information on how the name used for output is derived.
`namejoin` | Replace any spaces in the name with underscores. This is applied after the effect of any `nameparse` action. It is most useful with `nameparse=full`, and when the output format is such that having spaces in names is problematic.

`quantum`

The sequence contains quantum DNA. Note that this changes the game significantly, and many of LASTZ’s other actions and options are not valid with quantum sequences. Operations such as reverse complement, masking, special treatment of `N`s and `X`s, seeding options that need to recognize matches / transitions / transversions, and computation of percent identity do not apply because of the arbitrary quantum alphabet and the ability of its symbols to encode ambiguity.

`quantum=<code_file>` | The sequence contains quantum DNA corresponding to the specified `<code_file>`, which assigns nucleotide probabilities for the quantum alphabet. These are only used to augment the display of alignment blocks in the Human-Readable Text output format.

In addition to the sequence specifier syntax shown above, LASTZ supports a more complicated syntax. This is to maintain compatibility with BLASTZ and early versions of LASTZ. All of the functionality described here can be performed using the newer syntax above.

The complete format of a sequence specifier is

        [<nickname>::]<file_name>[/<select_name>][{<mask_file>}][[<actions>]][-]

As with the simpler syntax, the `<file_name>` field is required; all other fields are optional. The `<file_name>` and `<actions>` fields have the same meaning as in the simpler syntax.

`<nickname>::` is equivalent to the `<name>` field in the `nickname=<name>` action.

`/<select_name>` is only valid for the 2Bit file format, and only when the file name ends with ".2bit". It specifies a single sequence from the file to use, rather than all sequences. This is similar to the `subset=<names_file>` action, except that here a single sequence name is given instead of a file of names. Note that the name must match the mangled sequence name extracted from the file.

`{<mask_file>}` is identical to the `xmask=<mask_file>` action.

A `-` (minus sign) is equivalent to swapping the endpoints in the `<subrange>` action; it causes the reverse complement of the sequence to be used instead of the sequence itself. Again, this should be used with care, as it can lead to murky interactions with other features. In BLASTZ it was needed for searching only the minus strand, but LASTZ provides a `‑‑strand` option for that.

## Processing Stages in Detail

### Target Sequence Input

The target sequence is read at the beginning and kept in memory throughout the run of the program. Actions such as masking, unmasking, or reverse complement are applied when the file is read. If there are multiple sequences in the target file, they are treated internally as one long sequence (you must use the `multiple` action in the target file’s sequence specifier to enable this).

In contrast, queries are processed individually and sequentially. Each query sequence is read just before its seeding stage. The seeding through output stages are performed, comparing the query to the target. Then by default, the same stages are repeated to compare the reverse complement of the query to the target, before moving on to the next sequence in the query file.

### Scoring Inference

Scoring inference is not normally performed. As described in Inferring Score Sets, LASTZ can iteratively perform the complete alignment process on the target and query, to derive a suitable scoring set. This is only available for special builds of LASTZ, and will usually be too time-consuming to perform for all sequences being aligned. The typical application is to use it once on some sample sequences from the species of interest, save the scoring file, then use that scoring file for subsequent alignments.

### Indexing Target Seed Words

This pre-processing stage parses the target sequence(s) into overlapping seed words of some constant length (you can think of these as 12-mers; the actual length is determined by the seed pattern). Each word is converted to a number, called the packed seed word, according to the specified seed pattern. These (word, position) pairs are collected into the target seed word position table. Conceptually, this table is a mapping from a packed seed word to a list of the target sequence positions where that seed word occurs.

This table is one of the major space requirements of the program. Both the memory and time required for seeding can be decreased by using sparse spacing. The `‑‑step` option sets a step size: instead of examining every position, seed words are stored only for multiples of the step size. Large step sizes (say, `‑‑step=100`) incur a loss of sensitivity, at least at the seeding stage. However, to discover any gapped alignment block we only need to discover one seed (of many) in that alignment, so the actual sensitivity loss is small in most cases. Section 6.2 of [Harris 2007] discusses some experimental results on the effect of step size on the end result.

The presence of biological repeats in the target and query can also be addressed during the building of the position table. A large number of repeats can adversely affect the speed of the program, by increasing the number of irrelevant alignments the program considers in the early stages. LASTZ has three techniques for dealing with repeats.

1. Bases in the target and/or query sequences can be marked as repeats in advance, by using lower case. Target and query words containing lower case bases are left out of the seed word position table and skipped during seeding, respectively, so they do not participate in the seeding stage.
2. If repeat locations are not known, the option `‑‑maxwordcount` can be used to remove frequently occurring target seed words from the position table before query processing begins.
3. Dynamic masking (`‑‑masking`) can be used to mask target positions that have occurred in too many alignments; however this only affects subsequent query sequences.

### Seeding

Seeds are short near-matches between target and query sequences. They identify likely regions of homology that warrant further investigation, and serve as starting points for bootstrapping the alignment process. "Short" typically means less than 20 bp. Early alignment programs used exact matches (e.g. of length 12) as seeds, but more recent programs have used spaced seeds (these are described in more detail in the Seed Patterns section). For the purposes of this section, a seed can be thought of as a 12-mer exact match.

To locate seeds, the query sequence is parsed into seed words the same way the target is (except that `‑‑step` does not apply to the query; we look at every seed word). Each packed seed word is used as an index into the target seed word position table to find the target positions that have a seed match for this query position. Query seed words containing lower case bases are skipped, so that repeats will not participate in the seeding stage.

#### Quantum Seeding:

For alignments with quantum DNA it is not possible to do a direct lookup into the target seed word position table. The position table is for DNA words (consisting of `A`, `C`, `G`, and `T`), whereas the query consists of symbols from an arbitrary alphabet. The quantum sequence is parsed into seed words as before, but instead of a direct lookup, each word, called a q-word, is first converted to a quantum seeding ball of those DNA words that are most similar to it. Similarity is determined by the scoring matrix; all words with a combined substitution score above the quantum seeding threshold (set by the `‑‑ball` option) are considered to be in the ball. Then each word in the ball is looked up in the target seed word position table as usual, with all such hits considered to be seed matches for the q-word.

The quantum seeding threshold can also be set as a percentage of the maximum word score possible. If an exact match seed is used, the maximum word score is the highest value in the substitution matrix multiplied by the seed length. If a spaced seed is used, the multiplier is the number of `1` positions in the pattern.

Note that the seeding options that provide special treatment for transitions (`T`s in the seed pattern, half-weight seeds, allowing one or two match positions to be transitions, etc.) are not supported for quantum alignments. These options would make the quantum seeding procedure more complex, and are not really necessary because the quantum mechanism itself provides an alternative way to increase the alignment sensitivity. Also note that q-words containing lower case bases are not discarded, since the quantum alphabet is arbitrary and many ASCII bytes do not even have upper/lowercase versions.

### Gap-free Extension

In this stage, each seed is extended without allowing gaps to determine whether it is part of a high-scoring segment pair (HSP). The seed is extended along its DP matrix diagonal independently in both directions according to an extension rule, currently either exact match, M-mismatch, or x-drop.

Exact match extension (`‑‑exact`) simply extends the seed until a mismatch is found. If the resulting length is enough, the extended seed is kept as an HSP for further processing. Exact match extension is most useful when the target and query are expected to be very similar, e.g. when aligning short reads to a similar reference genome.

M-mismatch extension (`‑‑<M>mismatch`) extends the seed to find the longest interval that includes the entire seed and contains no more than `M` mismatches. If the resulting length is enough, the extended seed is kept as an HSP for further processing. M-mismatch extension is most useful when the approximate divergence between the target and query is known, and HSPs of a known length are desired. It provides a way to specify both length and identity thresholds together, with more flexibility than `‑‑exact`.

In x-drop extension (`‑‑xdrop`), as we extend in each direction we track the cumulative score for the extended match according to the substitution scoring matrix. The extension is stopped when the score drops off by more than the given x-drop threshold; that is, when the difference between the peak score seen so far and the current score is more than `<dropoff>`. (Another way to think of it is that the segment ends when a section scoring worse than −`<dropoff>` is encountered.) The extension is then trimmed back to the peak point. If the combined score of the seed plus both extensions meets the threshold set by the `‑‑hspthresh` option, it qualifies as an HSP and is kept for further processing. Matches that do not meet the score threshold are discarded. The `‑‑entropy` options control whether or not the scores are adjusted for nucleotide entropy when they are compared to the threshold.

#### Adaptive Score Threshold:

Often it is not clear in advance what value to use for the x-drop method’s HSP score threshold — set it too high and hardly anything will align, but too low and the program will be swamped and not finish. LASTZ’s adaptive scoring options (`‑‑hspthresh=top<basecount>` and `‑‑hspthresh=top<percentage>%`) allow you to set the threshold indirectly to align the desired amount of the target (as an approximate number of bases or as a percentage, respectively). This way you can set it for, say, 10% (which will run quickly regardless of the data), then examine the scores in those results and make an informed choice for your real threshold.

#### Diagonal Hashing:

LASTZ includes a time and space optimization that deals with multiple seeds in the same HSP. The number of seeds in an HSP is generally proportional to both the length of the HSP and the similarity of the sequences being compared. For long HSPs or very similar sequences, performing extension over and over for many seeds in the same HSP would adversely affect the run time. To prevent this, LASTZ maintains a diagonal extent table that tracks the latest seed extension on each diagonal (only the latest is needed because of the way the seeds are sorted). As new seeds "arrive", if they overlap an earlier extension, they are simply ignored. While this saves time, a direct implementation could require a lot of space. For two human chromosomes of size 250M bp, the DP matrix has 500 million diagonals, and storing one position for each diagonal would require 2G bytes. To save memory, LASTZ hashes diagonals to 16-bit values and tracks extensions only by the hash value. While this saves space, it results in a miniscule loss of sensitivity — LASTZ may miss some seeds due to hash collisions. Using `‑‑recoverseeds` will prevent losing these seeds, but will slow the program significantly. Moreover, since most true alignments contain many HSPs, with many seeds in each HSP, the vast majority of lost seeds have no effect on the final results.

### HSP Chaining

The chaining stage aims to find a series of HSPs that forms a high-scoring path through the DP matrix, aligning as much as possible while avoiding backtracking in either sequence. Conceptually it does this by examining all combinations of HSPs and scoring the chains according to the relative positions of the HSPs (e.g. the distances between them along the diagonal and anti-diagonal) as well as their individual scores. All HSPs not in the highest-scoring chain are discarded.

Ideally this process selects the "real" alignments, filtering out noise (such as extra alignments due to repeats), and producing a set of HSPs where each base is aligned at most once; however this is not guaranteed. LASTZ’s implementation is primarily intended for the case where elements are known to appear in the same relative order and orientation in the query as in the target. (However, note that because the forward and reverse strands are processed in separate pipelines, it will not necessarily cause inversions to be discarded.) If LASTZ’s implementation of chaining is not suitable, it is possible to substitute another chaining program by first running LASTZ with the `‑‑nogapped` and `‑‑writesegments` options to get the HSPs, running a separate chaining program to filter them, and then running the final stages of LASTZ on that output via the `‑‑segments` option.

Figure 5(a) shows an alignment without chaining, while 5(b) shows the same alignment with chaining.

Figure 5(a)

    lastz target query --nochain

Figure 5(b)

    lastz target query --chain

### Gapped Extension

Before the HSPs are extended further by allowing gaps, each HSP is first reduced to a single anchor point; this allows for the possibility that the optimal alignment may include gaps within the region occupied by the HSP. The gap-free HSP is only an indication of likely homology in that vicinity; other paths through the same region that allow gaps may have a higher score, so we don't want to just extend from the ends of the HSP. Instead we run the gapped algorithm from a single point that we think is most likely to lie on the optimal path, namely the middle of the highest-scoring 31-bp interval in the HSP. A more general (and expensive) approach would be to examine all paths through the square region defined by the HSP, instead of starting from a single anchor point.

Figure 6(a) illustrates the relationship of seeds, HSPs, and anchors. Heavy lines are seeds, which were extended without gaps (see Overview) to create HSPs (thin lines). Blue dots are anchors. Seeds with no HSP shown (gray lines) had low-scoring extensions and were discarded at the gap-free extension stage.

Figure 6(a) |  | Figure 6(b)

The anchors are then processed in the order of their HSP’s score (highest first). Gapped extension is performed independently in both directions from the anchor point, and the two resulting alignments are joined at the anchor. If the total score meets the threshold specified by the `‑‑gappedthresh` option, the joined alignment is kept and passed to the next stage; otherwise it is discarded. If the extension from one anchor happens to go through one or more other anchors, the redundant anchors are dropped from the list.

Figure 6(b) shows the relationship of anchors and their gapped extensions. The blue dots are the anchors from 6(a), which are extended in both directions to form gapped alignments (squiggly lines; the gaps are too small to be visible at this scale). One anchor had low-scoring extensions that did not meet the threshold. Another had an extension that ran directly through a nearby anchor; that anchor did not need to be processed separately.

The gapped extensions are computed using a typical dynamic programming recurrence for affine gap alignment (e.g. [Myers 1989] or [Gusfield 1997]), beginning at the anchor and terminating at the point with the highest cumulative score. The portion of the DP matrix examined is reduced by disallowing low-scoring regions (see [Zhang 1998]): wherever the alignment score drops below the peak score seen so far by more than the threshold specified in the `‑‑ydrop` option, the DP matrix is truncated and no further cells are computed along that row or column. By default the extension is then trimmed back to the location of the peak score; thus the extension normally ends when all remaining sub-alignment possibilities (paths in the DP matrix) begin with sections that score worse than −`<dropoff>`. However for alignments where the extension reaches the end of the sequence, you can suppress this trimming by specifying the `‑‑noytrim` option, which is recommended when aligning short reads.

Figure 7 shows the effect of the y-drop threshold in more detail. Extension is performed in two directions from the anchor (in this example, to the upper right and lower left, because both sequences are on the positive strand). The gray region is the portion of the DP matrix explored by the extension algorithm; its boundary is formed by the points where the score dropped from the maximum by more than the y-drop threshold.

Figure 7

### Back-end Filtering

Whatever alignment blocks have made it through the above gauntlet are then subjected to identity, continuity, coverage and match count filtering (as specified by the `‑‑filter=identity`, `‑‑filter=continuity`, `‑‑filter=coverage`, `‑‑filter=nmatch`, `‑‑filter=nmismatch`, `‑‑filter=ngap`and `‑‑filter=cgap` options, respectively). Blocks that do not meet the specified range for each feature are discarded.

Identity is the fraction of aligned bases (excluding columns containing gaps or non-ACGT characters) that are matches, expressed as a percentage. The numerator is the number of matches in the alignment block, while the denominator is the number of matches plus the number of mismatches. Characters that differ only in upper vs. lower case are counted as matches. Columns containing gaps or non-ACGT characters play no part in this computation, and it is independent of the settings for `‑‑ambiguous=n` and `bad_score`. Identity cannot be determined for alignments with quantum DNA, because of the potential ambiguity of the symbols.

Continuity is the fraction of alignment columns that do not contain gaps, expressed as a percentage. The numerator is the number of matches plus mismatches in the alignment block, while the denominator is the number of columns. Unlike the computation of identity, here "matches plus mismatches" includes all non-gap columns regardless of whether they contain non-ACGT characters.

Coverage is the fraction of bases in the entire input sequence (target or query, whichever is shorter) that are included in the alignment block, expressed as a percentage. Such bases are aligned in the block to either bases or gaps in the other sequence. Note that if there are multiple sequences in the target and/or query, only the current one is considered; however if an input sequence is spliced with runs of `N`s or `X`s, then the combination of all its subsequences (including the splice characters between them) is considered as one input sequence, because LASTZ does not explicitly recognize the splicing. Further, if a separator character is used, again the combination of all subsequences is considered as one input sequence (including the separator characters). Also note that each block’s coverage is computed independently of other blocks, and each must meet any specified filter range by itself; blocks cannot be combined to meet coverage requirements.

Match Count, or nmatch, is the number of matched bases in the alignment. Characters that differ only in upper vs. lower case are counted as matches, columns containing gaps or non-ACGT characters are not. Match count cannot be determined for alignments with quantum DNA, because of the potential ambiguity of the symbols.

Mismatch Count, or nmismatch, is the number of aligned bases in the alignment that are not matches. This includes substitutions as well as non-ACGT characters (even if they are identical), but not gaps. Mismatch count cannot be determined for alignments with quantum DNA, because of the potential ambiguity of the symbols.

Gap Count, or ngap, is the number of gaps in the block, counting each run of gapped columns as a single gap.

Gap Column Count, or cgap, is the number of gaps in the block, counting each gapped column as a separate gap.

### Interpolation

Once the above stages have been performed, it is not uncommon to have regions left over in which no alignment has been found. In the interpolation stage (activated by the `‑‑inner` option) we repeat the seeding through gapped extension stages in these leftover regions, at a presumably higher sensitivity. Using such high sensitivity from the outset would be computationally prohibitive (due to the excessive number of false, low-scoring matches), but is feasible on the smaller, leftover regions.

Another complete alignment round (seeding, gap-free extension, chaining, and gapped extension, even if some of these were skipped in the main alignment; but not back-end filtering) is performed in the small areas between the alignment blocks found in the preceding main alignment stage. Only regions within 20K bp from the endpoints of the passed-in alignment blocks are searched. Seeding for this alignment requires a 7-bp exact match with no transitions, and uses the specified scoring threshold for both its gap-free and gapped extension sub-stages. (This threshold should generally be set lower than the corresponding ones in the main alignment, in order to increase the sensitivity of the interpolation.) All other parameters are the same as those used for the main alignment stages.

Figure 8 shows the operation in more detail. The alignment blocks resulting from gapped extension are shown in 8(a) as squiggly lines. After interpolation, in 8(b), additional alignment blocks have been discovered in the red areas. Note that there are still some holes remaining, where these sequences just don't align well.

Figure 8(a)

    lastz target query

Figure 8(b)

    lastz target query --inner=1000

### Alignment Output

The alignment blocks found by the preceding pipeline of stages are written to `stdout` (or to a file specified with the `‑‑output` option) in the requested format. These may be seeds, gap-free HSPs, or gapped local alignments, depending on which stages were performed. There is no particular order to the alignment blocks for an individual query sequence (e.g. they are not sorted by score or position). However, since the query sequences are processed serially, the blocks for each one will appear together in the output.

## File Formats

LASTZ typically receives two sequence files and possibly a scoring file as inputs, and produces an alignment file as output.

DNA sequences can be provided in FASTA, FASTQ, Nib, or 2Bit format, or indirectly via an HSX index. These sequences contain a series of `A`, `C`, `G`, `T`, and `N` characters in upper or lower case. Lower case indicates repeat-masked bases, while `N`s represent unknown bases if the `‑‑ambiguous=n` option is specified. (By default, a run of `N`s or `X`s is used to separate sequences that have been catenated together for processing, but this is now deprecated; see Non-ACGT Characters, Splicing, and Separation for a discussion of the use of `N`s and `X`s.) As an alternative to DNA sequence, quantum DNA using an abstract alphabet can be used as the query (but not as the target).

The FASTA, FASTQ, 2Bit and HSX formats support more than one sequence within the same file. Files containing multiple sequences are normally only used as the query; however invoking the `multiple` action in the file’s sequence specifier allows them to be used for the target as well. Also, the `subset` action allows one or more sequences to be selected from such a file.

The FASTQ format carries base-calling quality values as well as DNA.

### FASTA (sequence input)

FASTA format stores DNA sequences as plain text. The first line begins with a `>` followed by the name of the sequence, and all subsequent lines contain nucleotide characters. The lines can be of any length. If the file contains multiple sequences, each should start with its own `>` header line. NCBI FASTA specification

Note that although the official FASTA specification allows the character `X` only in amino acid sequences, LASTZ accepts it in DNA sequences as a splicing character. However, LASTZ does not currently support IUPAC-IUB ambiguity codes other than `N` (such as `R`, `W`, etc.), beyond the treatment afforded by `‑‑ambiguous=iupac`.

A special case, non-conforming to the official standard, is made to allow a special user-specified separator character. Usually this will be `N` or `X`, but any other printable ASCII character that suits the user’s needs is acceptible.

It has become common for suppliers of FASTA files to pack a plethora of additional information into a sequence’s header line. This extra information can create difficulties for many sequence processing tools. For example, headers often contain spaces but file formats such as MAF do not allow spaces in sequence names. To compensate for this, LASTZ provides several options for extracting a concise name from sequence headers; see Sequence Name Mangling for details.

### FASTQ (sequence input)

FASTQ format stores DNA and base-calling quality sequences as plain text, and is primarily used to describe the results of short-read sequencing runs. As explained in [Cock 2009], this format has evolved over time in the Bioformatics community. LASTZ only supports a subset of this format, prohibiting line-wrapping within DNA or quality sequences.

Each sequence consists of four lines. The first line begins with a `‑` followed by the name of the sequence. The second line contains nucleotide characters. The third line begins with a `+`, optionally followed by the name of the sequence (which, if present must match that of the first line). The fourth line contains quality characters.

There are several conflicting standards for encoding quality values in FASTQ files, but (as of this writing) the differences are not relevant to LASTZ. LASTZ currently does not make any computational use of the qualities, and simply copies them into the output file when appropriate.

LASTZ treats IUPAC-IUB ambiguity codes in FASTQ files the same as those in FASTA files.

### Nib (sequence input)

Nib format stores a single unnamed DNA sequence, packed as two bases per byte. UCSC Nib specification

### 2Bit (sequence input)

2Bit format stores multiple DNA sequences, encoded as four bases per byte with some additional information describing runs of masked bases or `N`s. UCSC 2Bit specification

Sequence names in 2Bit files have all the same problems as in FASTA files, so Sequence Name Mangling applies to these files as well.

### Quantum DNA (sequence input)

A quantum DNA file describes a single sequence of "quantum" DNA, which uses an abstract, user-defined alphabet. Each position in the sequence is a byte with a value in the range `0x01`..`0xFF`, which can represent an ambiguity code, amino acid, or any other meaning you desire. LASTZ does not try to interpret these in any way; it just aligns them as abstract symbols corresponding to columns in the scoring matrix. Note that the value `0x00` is prohibited.

The file itself is stored in a binary format described by the table below. It can be written on either a big-endian or little-endian machine; LASTZ determines the byte order of multi-byte fields by examining the magic number at the start of the file. Be sure to use the `quantum` action in the file’s sequence specifier to notify LASTZ that it contains quantum DNA.

File Offset | Data | Meaning
`0x00` | `C4 B4 71 97` —or— `97 71 B4 C4` | Magic number indicating big-endian byte order. Magic number indicating little-endian byte order.
`0x04` | `00 00 02 00` | File conforms to version 2.0 of the Quantum DNA file format.
`0x08` | `00 00 00 14` | Header length in bytes, including this field through the all-zero field.
`0x0C` | `xx xx xx xx` | `SOFF`: offset (from file start) to sequence data.
`0x10` | `xx xx xx xx` | `NOFF`: offset (from file start) to name; 0 indicates no name.
`0x14` | `xx xx xx xx` | `SLEN`: length of sequence data.
`0x18` | `00 00 00 00` | Must be zero.
`NOFF` | … | Name: a zero-terminated ASCII string.
`SOFF` | … | Sequence data: a series of `SLEN` bytes, each of which is one quantum symbol in the sequence.

### Quantum Code File

This file is used with the `quantum` action in a sequence specifier. It defines a mapping from quantum DNA symbols to vectors of values for the four nucleotides `A`, `C`, `G`, and `T`. Usually these indicate the nucleotide probability distribution for each symbol in the quantum alphabet. However, LASTZ doesn't interpret the values, and only uses them to to augment the display of alignment blocks in the Human-Readable Text output format.

Each line in the file gives the mapping for one symbol. Lines beginning with a `#` are considered to be comments and are ignored, as are blank lines. Data lines have five columns, separated by whitespace. The first field contains the symbol, as either a single character or two hexadecimal digits, while the remaining four fields contain values for `A`, `C`, `G`, and `T`, respectively. Each value can be either a single floating-point number or a fraction (two floating-point numbers with a `/` between them, without spaces). Any symbols in the quantum alphabet that aren't listed in this file receive zeroes for all four values.

Here is an example.

        # sym p(A|sym) p(C|sym) p(G|sym) p(T|sym)
          01  0.125041 0.080147 0.100723 0.694088
          02  0.111162 0.053299 0.025790 0.809749
          03  0.065313 0.007030 0.004978 0.922679
           ... more rows here ...
          FF  0.209476 0.014365 0.755682 0.020477

### Sequence Name File

This file is used with the `subset` action in a sequence specifier to select particular sequences for processing. It consists of one sequence name per line. Lines beginning with a `#` are considered to be comments and are ignored, as are blank lines. Only the first whitespace-delimited word in any line is read as the name; the rest of the line is ignored.

Note that when used in conjunction with a FASTA or 2Bit file, the names must appear in the same order as they appear in the corresponding sequence file, and must match the mangled name extracted from that file. When used with an HSX file, the names can be in any order but must match names indexed in the HSX file.

### Sequence Masking File

This file is used with the `xmask` and `nmask` actions in a sequence specifier. It can also be created by using the `‑‑outputmasking=<file>` or `‑‑outputmasking:soft=<file>` options. It consists of one interval per line, without sequence names. Lines beginning with a `#` are considered to be comments and are ignored, as are blank lines. Only the first two whitespace-delimited words in any line are interpreted as the interval; the rest of the line is ignored.

Each interval describes a region to be masked, and consists of

        <start> <end>

Locations are one-based and inclusive on both ends (i.e., they use the origin-one, closed position numbering system). Note that the masking intervals are counted along the forward strand, even if we are only aligning to the reverse complement of the query specifier (i.e. for `‑‑strand=minus`).

Here is an example. If the target sequence is hg18.chr1, this would mask the 5' UTRs from several genes. Note that the third column is neither required nor interpreted by LASTZ, and acts as a comment.

         884484  884542  NM_015658
         885830  885936  NM_198317
         891740  891774  NM_032129
         925217  925333  NM_021170
         938742  938816  NM_005101
         945366  945415  NM_198576
        1016787 1016808  NM_001114103
        1017234 1017346  NM_001114103
        1041303 1041486  NM_001114103

### Sequence Masking File, Three Fields

This file format is output only. LASTZ does not recognize input files in this format.

This file is created by using the `‑‑outputmasking+=<file>` or `‑‑outputmasking+:soft=<file>` options. It consists of one interval per line, with sequence names.

Each interval describes a region that has been masked, and consists of

        <name> <start> <end>

Locations are one-based and inclusive on both ends (i.e., they use the origin-one, closed position numbering system). Note that the masking intervals are counted along the forward strand, even if we are only aligning to the reverse complement of the query specifier (i.e. for `‑‑strand=minus`).

### Scoring File

This file is used with the `‑‑scores` option to specify a set of (mostly) scoring-related parameters en masse. The score set consists of a substitution matrix and other settings. The other settings come first and are individually explained in the table below. All settings are optional, and most of them have exact correspondence to command-line options and the same defaults (unless otherwise specified in the table). Command-line settings always override settings in this file. Any line may end with a comment (`#` is the comment character).

In the matrix, rows correspond to characters in the target sequence, while columns correspond to characters in the query. Matrix labels can be specified either as single ASCII characters or as two-digit hexadecimal values in the range `01`..`FF` (do not add a leading `0x`). Note that the value `00` is not allowed. The rows and columns of the matrix need not have the same set of labels, so for example, a matrix might describe scoring between the 4-letter DNA alphabet and the 15-letter ambiguity alphabet. Any labels other than `A`, `C`, `G`, and `T` (or their hex equivalents) are treated as quantum DNA.

Score values can be floating-point if the `lastz_D` version of the executable is used instead of `lastz`.

Here is an example:

        # This matches the default scoring set for BLASTZ

        bad_score          = X:-1000  # used for sub['X'][*] and sub[*]['X']
        fill_score         = -100     # used when sub[*][*] is not defined
        gap_open_penalty   =  400
        gap_extend_penalty =   30

             A     C     G     T
        A   91  -114   -31  -123
        C -114   100  -125   -31
        G  -31  -125   100  -114
        T -123   -31  -114    91

BLASTZ scoring files are also accepted. These only contain a substitution matrix, and row labels must be absent (they are assumed to be the same as the column labels). No other settings are allowed.

           A     C     G     T
          91  -114   -31  -123
        -114   100  -125   -31
         -31  -125   100  -114
        -123   -31  -114    91

Keyword | Setting | Meaning

`bad_score`

`<score>`
`<row>:<col>:<score>`

This score fills a single row and column of the substitution matrix, so that any occurrences of the corresponding characters are severely penalized. By default the "bad" character for both the target and query is `X` for DNA sequences or the null byte (`00`) for quantum DNA sequences, and the associated score is −1000.

This option allows you to change these characters and/or the score they receive. The <row> and <col> fields are character codes (as explained above); if they are absent `X` (and/or `00`) is assumed. Note that these characters are case sensitive. The bad_score row and column cannot be removed entirely, but you can achieve the same effect by setting them to invalid characters that will never occur in your sequences. There is no corresponding command-line option.

`fill_score` | `<score>` | This is used as a default for all cells of the scoring matrix that are not otherwise set (either by the user or by LASTZ’s defaults). This is the score used for `N`s (unless `‑‑ambiguous=n` is specified on the command line). The default value is −100. There is no corresponding command-line option.
`gap_open_penalty` | `<penalty>` | This is identical to the `<open>` field of the `‑‑gap` command line option.
`gap_extend_penalty` | `<penalty>` | This is identical to the `<extend>` field of the `‑‑gap` command line option.
`step` | `<offset>` | This is identical to the `‑‑step` command line option.
`seed` | `<strategy>` | This corresponds to the `‑‑seed` and `‑‑transition` command line options. `<strategy>` must be one of the following, with no spaces: `12of19,transition` `12of19,notransition` `14of22,transition` `14of22,notransition`
`ball` | `<score>` `<percentage>%` | This is identical to the `‑‑ball` command line option.
`x_drop` | `<dropoff>` | This is identical to the `‑‑xdrop` command line option.
`hsp_threshold` | `<score>` | This is identical to the `‑‑hspthresh` command line option, except that it does not currently support the `‑‑hspthresh=top<basecount>` or `‑‑hspthresh=top<percentage>%` variants.
`y_drop` | `<dropoff>` | This is identical to the `‑‑ydrop` command line option.
`gapped_threshold` | `<score>` | This is identical to the `‑‑gappedthresh` command line option.

### Inference Control File

When LASTZ is asked to infer substitution scores and/or gap penalties from the input sequences (e.g. via the `‑‑infer` option), this file is used to set parameters that control the inference process.

Here is an example (note that currently the parsing of this file is less flexible than some of the others, and `*` is the only arithmetic operator supported):

        # base the inference on alignments in the middle half by identity
        min_identity       = 25.0%    # 25th percentile
        max_identity       = 75.0%    # 75th percentile

        # scale scores so max substitution score will be 100, and only use
        # alignments scoring at least as well as 20 ideal matches
        inference_scale    = 100      # max substitution score
        hsp_threshold      = 20*inference_scale
        gapped_threshold   = hsp_threshold

        # allow substitution score inference to iterate at most 20 times;
        # don't perform gap penalty inference -- instead hardwire gap penalties
        # relative to max substitution
        max_sub_iterations = 20
        max_gap_iterations = 0
        gap_open_penalty   = 4*inference_scale
        gap_extend_penalty = 0.3*inference_scale

        # use all seedword positions (don't sample)
        step               = 1

        # adjust for entropy when qualifying HSPs
        entropy            = on

`min_identity` and `max_identity` specify the range of sequence identity upon which inference is based; only alignment blocks within this range contribute to the inference. If the value ends with a percent sign, it represents a percentile of the identity distribution over all the blocks; otherwise it is a fixed percent identity value. For example, `min_identity=70` and `max_identity=90` indicates that blocks with identity ranging from 70 to 90 percent will be used, while `min_identity=25%` and `max_identity=75%` indicates that half of the blocks will be used (from the middle of the distribution). The defaults are `min_identity=0` and `max_identity=100` (i.e., no blocks are excluded from inference due to percent identity).

`inference_scale` specifies a value for the largest substitution score (i.e., the score for the best match). All other scores are scaled proportionally. If this is set to `none`, the scores will be log-odds using base 2 logarithms. The default is `inference_scale=100`.

`hsp_threshold` and `gapped_threshold` correspond to the command line `‑‑hspthresh` and `‑‑gappedthresh` options. The defaults are `hsp_threshold=3000` and `gapped_threshold=hsp_threshold`.

`max_sub_iterations` and `max_gap_iterations` specify limits on the number of inference iterations that will be performed. For example, if you only want a substitution scoring matrix, you can set `max_gap_iterations=0`. The defaults are `max_sub_iterations=30` and `max_gap_iterations=0`.

`gap_open_penalty` and `gap_extend_penalty` correspond to the command line `‑‑gap=[<open>,]<extend>` option. These are used for the first iteration of gap-scoring inference. The defaults are `gap_open_penalty=3.25*worst_substitution` and `gap_extend_penalty=0.24375*worst_substitution`.

`step` corresponds to the command line `‑‑step` option. A large step, e.g. `step=100`, could potentially speed up the inference process. Ideally, this would base the inference on a sample of only one percent of the whole. However, the sample actually ends up larger than that and is biased toward HSPs that are either longer or have a lower substitution rate. This happens because sampling occurs at the seed level, and such HSPs generally have more seeds. Future versions of LASTZ may include a means to compensate for this bias. The default is `step=1`.

`entropy` corresponds to the command line `‑‑entropy` option. Legal values are `on` or `off`. If on, sequence entropy is incorporated when filtering HSPs. The default is `entropy=on`.

The value of `worst_substitution` cannot be set directly. Instead, it is computed from the initial scoring matrix. It is the minimum score in the scoring matrix for any of the symbols A, C, G or T (equivalently, the most negative score or the maximum penalty).

Note that these parameters apply to the inference process only. If the corresponding command line options are also set, those will apply for the final, "real" alignment stages (and will also override the inferred values if there is a conflict), but will not affect the inference itself. Inference cannot be used in conjunction with a scores file.

### HSX (Hashed Sequence Index)

An HSX file is an index of sequences in other files, allowing fast random access to those sequences. The current implementation of LASTZ only supports indexing FASTA files. Future versions may include Nib and 2Bit sequences. The following is a brief overview of the file format. For more detailed information, see the HSX specification

An HSX file can be created using the `build_fasta_hsx.py` utility (included in the `tools` directory of the LASTZ distribution), using a command like this:

        build_fasta_hsx sequences.fa [more_sequences.fa ...] > index.hsx

It is important that the HSX file has the extension `.hsx` and resides in the same directory as the files being indexed. Further, the files being indexed must have the extension `.fa` or `.fasta`. These rules allow LASTZ to determine the sequence file type when it reads the HSX file, and to locate the files containing the sequences.

The index file includes names to be used for the sequences, which do not have to match the original names or headers in the sequence files. This feature obviates the need for LASTZ to perform sequence name mangling, so most of those actions are not supported for HSX files. Instead, it is the responsibility of the program that creates the index to select suitable names.

### Target Capsule File

A target capsule file is essentially a memory dump of several internal data structures related to the target sequence and the target seed word position table. At the present time the authors do not wish to create an official specification for this format, but please see Using Target Capsule Files for information on how to create and utilize them.

### Alignment Chores File

A chores file describes a list of sequence interval pairs, indicating that the alignment process is to be restricted to those intervals.

The file contains two intervals per line, one from the target and one from the query, with sequence names. Optionally, the query strand can be specified, as well as an identifying tag. Lines beginning with a `#` are considered to be comments and are ignored, as are blank lines. `#` can also be used to put comments at the end of lines, but must be preceeding by whitespace.

Each line looks like

        <name1> <start1> <end1> <name2> [<start2> <end2>] [<strand2>] [id=<tag>] [#<comment>]

where <name1>, etc. correspond to the target sequence and <name2>, etc. correspond to the query. Fields are delimited by whitespace.

When the target name is irrelevant (i.e. when there is only one name in the target sequence file), `*` can replace <name1>. Similarly, if we don't have a target (or query) subrange, `* *` can be used in place of start and end. Note that the query subrange and strand are optional, as is the tag. When the strand is not specified, both strands are searched.

Locations are one-based and inclusive on both ends, i.e. origin-one, closed (thus the interval "154 228" has length 75 and is preceded by 153 bases in its sequence). All target intervals are on the positive strand. All query intervals are counted along the forward strand, regardless of which strand is specified.

Target sequence names may appear in any order. Sequence names for the query must appear in the same order as they do in the query file. Because alignment output ordering is on a chore-by-chore basis, it is good practice to include all positive strand intervals for a query before any negative strand intervals for that query. Some downstream tools may depend on this ordering.

The tag can be any short string the user wants to associate with the chore (excluding whitespace). As of this writing, the only use of the tag field is that it can be copied to the output file by use of the `chore` field for `‑‑format=general`.

Here is an example.

        chr9  116517410 116518409  READ_00070 *   *   + id=DFZ
        chr3  157707345 157708344  READ_00070 *   *   + id=EDZ
        chr9  112944437 112945436  READ_00078 101 200 + id=FAC
        chr1  3377578   3378577    READ_00078 *   *   + id=LLH
        chr2  175604671 175605670  READ_00078 *   *   - id=DFZ
        chr2  230613705 230614704  READ_00079           id=DFZ
        chr9  20387422  20388421   READ_00355 *   *   + id=DFZ
        chr8  16396215  16397214   READ_00355 *   *   + id=MNQ
        chr14 *         *          READ_00355 *   *   - id=MNQ
        chr4  50534096  50535095   READ_00355 *   *   - id=QOY
        chr6  58308766  58309765   READ_00376 *   *   - id=EDZ
        chr5  172249269 172250268  READ_00376 *   *   - id=FAC
        chr9  123860065 123861064  READ_00376 *   *   - id=MNQ

### Segment File

A segment file describes a list of segments representing gap-free alignments. This list is either produced internally by LASTZ as a result of the gap-free extension stage (see Overview), or read from a user-supplied file via the `‑‑segments` option. The latter causes LASTZ to skip the indexing, seeding, and gap-free extension stages and begin with the chaining stage (or the next specified stage, if chaining is not requested).

The file contains two intervals per line, one from the target and one from the query, with sequence names. Lines beginning with a `#` are considered to be comments and are ignored, as are blank lines. `#` can also be used to put comments at the end of lines.

Each line looks like

        <name1> <start1> <end1> <name2> <start2> <end2> <strand2> [<score>] [#<comment>]

where <name1>, etc. correspond to the target sequence and <name2>, etc. correspond to the query. Fields are delimited by whitespace.

Locations are one-based and inclusive on both ends, i.e. origin-one, closed (thus the interval "154 228" has length 75 and is preceded by 153 bases in its sequence). Negative strand intervals are measured from the 5' end of the query’s negative strand (corresponding to the rightmost end of the given query sequence, i.e. counted along the reverse strand). All target intervals are on the positive strand. The two intervals must have the same length (since these alignments are gap-free). The score is used to determine the processing order during gapped extension. Segments without scores are given a score of zero.

Query sequence names must appear in the same order as they do in the query file. For each query sequence, normally all positive strand intervals must appear before any negative strand intervals. Sequence names for the target may appear in any order, and are only meaningful if the `multiple` action is used; otherwise they are ignored. Intervals with names not found in the target or query are not allowed. In cases where sequence names are either unknown or of no importance (e.g. when all sequences in the file have the same name), a `*` can be used as a generic sequence name.

Here is an example.

        R36QBXA37A3EQH 151 225  Q81JBBY19D81JM 14  88 +  6875
        R36QBXA37D4L6V  26 100  Q81JBBY19D81JM 10  84 +  6808
        R36QBXA37EVLNU  19  93  Q81JBBY19D81JM  7  81 +  6842
        R36QBXA37CEBPD   8  81  Q81JBBY19D81JM  9  82 +  7108
        R36QBXA37BLO6X 132 205  Q81JBBY19D81JM 11  84 -  7339
        R36QBXA37A2W3P 162 214  Q81JBBY19D81JM  2  54 -  5024
        R36QBXA37A9395  62 136  Q81JBBY19A323K 18  92 +  7231
        R36QBXA37DNC74  18  82  Q81JBBY19A323K  2  66 +  6418
        R36QBXA37CTR26  83 167  Q81JBBY19ASA7F 19 103 +  8034
        R36QBXA37C2TAC  95 181  Q81JBBY19ASA7F 15 101 +  8272

### LAV (alignment output)

LAV is the format produced by BLASTZ, and is the default. It reports the alignment blocks grouped by "contig" (chromosome, scaffold, read, etc.) and strand, and describes them by listing the coordinates of gap-free segments. This format is compact because it does not include the nucleotides, but consequently interpretation usually requires access to the original sequence files, and it is not easy for humans to read. LAV specification (same specification at PSU)

The option `‑‑format=lav+text` adds textual output for each alignment block (in the same format as the `‑‑format=text` option), intermixed with the LAV format. Such files are unlikely to be recognized by any LAV-reading program.

### AXT (alignment output)

AXT is a pairwise alignment format popular at UCSC and PSU. UCSC AXT specification

The option `‑‑format=axt+` reports additional statistics with each block, in the form of comments. The exact content of these comment lines may change in future releases of LASTZ.

### MAF (alignment output)

MAF is a multiple alignment format developed at UCSC. The MAF files produced by LASTZ have exactly two sequences per block: the first row always comes from the target sequence, and the second from the query. UCSC MAF specification

The option `‑‑format=maf+` reports additional statistics with each block, in the form of comments. The exact content of these comment lines may change in future releases of LASTZ.

The option `‑‑format=maf-` suppresses the MAF header and any comments. This makes it suitable for concatenating output from multiple runs.

UCSC’s MAF should not be confused with other formats that have the same name. For example, the MIRA sequence assembler project has a file format named MAF, but it is a completely unrelated file format and is not supported by LASTZ.

### SAM (alignment output)

SAM is a pairwise alignment format used primarily for short-read mapping, and supported by the SAMtools programming suite. This format is described in [Li 2009], and as of Feb 2015 a specification for it can be found at the Sequence Alignment/Map Format Specification in the SAMtools github repository.

For SAM files, LASTZ assumes that the target sequence is the reference and that query sequence(s) are short reads. For alignments that don't reach the end of a query, `‑‑format=sam` uses "hard clipping", while `‑‑format=softsam` uses "soft clipping". See the section on "clipped alignment" in the SAM specification for an explanation of what this means.

The option `‑‑eqx` causes CIGAR strings to use the operators "=" and "X" instead of the ambiguous "M" operator. Equivalently, the string "+eqx" can be attached to the SAM format option, e.g. `‑‑format=sam+eqx` or `‑‑format=softsam+eqx`.

The options `‑‑format=sam-` and `‑‑format=softsam-` suppress the SAM header lines. This makes them suitable for concatenating output from multiple runs.

### CIGAR (alignment output)

CIGAR is an acronym for Concise Idiosyncratic Gapped Alignment Report, a pairwise alignment format defined originally by the Exonerate alignment program. The format has since been adapted in different forms, as ensembl cigar format and as an extended cigar string in SAMtools. For `‑‑format=cigar`, LASTZ implements Exonerate CIGAR. LASTZ implements other CIGAR variants for `‑‑format=sam` and as fields for `‑‑format=general`.

Exonerate CIGAR format does not include nucleotides; instead it describes the locations of indels (but not substitutions) using run-length encoding. An alignment is characterized as runs of `M` (match and/or substitution), `I` (query contains a base not in target), and `D` (target contains a base not in query). Each run is encoded by the letter code, whitespace, and the length; multiple runs are separated by whitespace. The format also includes positional information for the start of the alignment. An `example` is shown at the end of this section. While there seems to be no complete, definitive specification for CIGAR, the CIGAR files produced by LASTZ are believed to match the format produced by Exonerate.

In the other variants of CIGAR, whitespace is removed and the order of the letter code and length are reversed (length appears before letter code). In some variants the length is omitted if it is 1; in other variants `M` runs are divided into `=` (match) and `X` (substitution). SAMtools extended cigar strings allow `S` and `H` runs to describe clipping operations for short sequences. LASTZ implements combinations of these variants where appropriate; details are described in `‑‑format=general:cigar`, `‑‑format=general:cigarx` and `‑‑format=sam`.

To understand the differences between different types of CIGAR strings, consider the following alignment of a short 61-bp query to a longer target.

        target:  ...GATTAAGAGTCTGTCCGACCTTCTTCT---GGGTTTACCGAAGCCCACTTAGCTGATATTCGA...
                       ||||||||||||||||X|||||||   |||||||  X||||||||||||||||||
         query:     ACCTAAGAGTCTGTCCGACATTCTTCTACGGGGTTTA--TAAGCCCACTTAGCTGATAAGGTT
                       ↑      1         2         3           4         5    ↑    6
                    0123456789012345678901234567890123456--789012345678901234567890

For `‑‑format=cigar`, the alignment would be described by this line:

        cigar: query 3 56 + target <start> <end> <strand> <score> M 24 I 3 M 7 D 2 M 19

For `‑‑format=general:cigar`, the alignment path would be described by this field:

        24M3I7M2D19M

For `‑‑format=general:cigarx`, the alignment path would be described by this field:

        16=X7=3I7=2DX18=

For `‑‑format=sam`, the alignment path would be described by this field:

        3H24M3I7M2D19M5H

### BLASTN (alignment output)

Note: Prior to release 1.04.22, this format reported query positions incorrectly when alignments were on opposite strands.

The BLASTN format reports pairwise alignments in a format similar to NCBI’s BLASTN program. Output is modeled upon version 2.2.24+ of the standalone version of BLASTN available from NCBI’s BLAST ftp site. (Note: that version of BLASTN is no longer available.) Output should be similar that produced by the command

        blastn -task blastn -db <target> -query <query> -outfmt 7

It is important to realize that a couple of the fields, specifically `evalue` and `bit score`, are written as crude approximations of the value that BLASTN would produce, as described below.

The format is tab-delimited with one alignment reported per line, plus an additional header. Here is some sample output:

        # lastz --format=blastn
        # Query: orange
        # Database: apple
        # Fields: query id, subject id, % identity, alignment length, mismatches, gap opens, q. start, q. end, s. start, s. end, evalue, bit score
        orange apple 82.14  2072 142 67 2    1926 103  2093 0     1972
        orange apple 100.00 14   0   0  1906 1919 2086 2073 0.043 26.5
        orange apple 93.33  15   1   0  1763 1777 2004 1990 0.53  22.9

Most of the fields correspond directly to fields available in the General output format. These are `query id=name2`, `subject id=name1`, `%identity=blastid%`, `alignment length=ncolumn`, `mismatches=nmismatch`, `gap opens=ngap`, `q.start=start2`, `and q.end=end2`. The fields `s.start` and `s.end` are nearly equivalent to `start1` and `end1`, but when the alignment is to the reverse strand, they appear in the other order (i.e. `s.start` > `s.end`).

The two remaining fields, evalue and bit score, are crudely estimated from LASTZ’s `score` field, but are not strictly correct. Further, these approximations assume that default LASTZ scores are used. Otherwise they are unlikely to be good approximations. The approximation formulas are

         evalue    = 3.0e9*exp(-0.01421*score)
         bit score = 0.0205*score

### PAF (alignment output)

The PAF format reports pairwise alignments in a format compliant with minimap2, available from the minimap2 github site. A simple spec for PAF files can be found here, while more detail can be found here.

LASTZ currently doesn't compute mapping quality scores, and reports 255 (missing) for the mapping quality field (column 12).

The PAF spec allows for certain SAM-like tags to be included. LASTZ produces two such tags — `AS` reports the lastz alignment score and `cg` reports the alignment's CIGAR string.

Two variations of the format are provided, to support two different formats for the CIGAR field. For `‑‑format=PAF` the CIGAR string does not distinguish matches from substitutions, which is what minimap2 produces. For `‑‑format=PAF:wfmash` the CIGAR string does distinguish matches from substitutions.

### Differences (alignment output)

LASTZ’s Differences format reports each difference between target and query on a separate line, where a difference is any indel or run of mismatches. It is intended for comparisons between close sequences, such as when comparing reads from a human individual to the human reference genome, or reads from a bacterial strain to a reference sequence for the same bacterium. The format is a tab-delimited table with one line per difference; it is well-suited for use with spreadsheets and the R statistical package.

The columns reported in this format are the name, start & end of the difference, strand, and overall size for the target; the name, start & end of the difference, strand, and overall size for the query; the text of the difference in the target, then in the query; and finally the text of the complete alignment block containing the difference, first in the target, then in the query. Intervals are origin-zero, half-open and counted along the forward strand.

The example below compares output in this format to similar results using the General output format for the same input sequences. For the Differences output, column numbers have been added for discussion (they are not in the actual output file). Each line in the output represents slight evidence that a mutation occurred changing the target sequence (chr22 here) to the query sequence (column 6). Columns 11 and 12 indicate the specific mutation that has putatively occurred. For example, the first line suggests that either an A has been inserted into chr22 at position 14485783, or an A has been deleted from EAYGRGI02GQ0SL at position 167 (actually, between positions 166 and 167). Note that there are three differences reported for EAYGRGI02GQ0SL, so it appears on three lines. The fifth line shows a putative SNP at chr22 position 15234401, with a C in the reference and a G in the read, while the seventh line shows evidence for an inversion of neighboring bases (AG vs. GA). Note that there are no lines for EAYGRGI01BIQCW, indicating a perfect match for that block (i.e., no differences).

Sample output for `‑‑format=differences`.

         (1)     (2)      (3)  (4)   (5)         (6)       (7) (8) (9) (10) (11)(12)  (13)     (14)
        chr22 14485783 14485784 + 49691432  EAYGRGI02GQ0SL 167 167  +  303   A   -   TGAGA... TGAGA...
        chr22 14485791 14485792 + 49691432  EAYGRGI02GQ0SL 174 174  +  303   A   -   TGAGA... TGAGA...
        chr22 14485843 14485843 + 49691432  EAYGRGI02GQ0SL 225 226  +  303   -   A   TGAGA... TGAGA...
        chr22 14731895 14731895 + 49691432  EAYGRGI01EAV19 228 229  -  298   -   A   CTTCT... CTTCT...
        chr22 15234401 15234402 + 49691432  EAYGRGI02H5ZGS 99  100  -  180   C   G   CGAAT... CGAAT...
        chr22 15255536 15255537 + 49691432  EAYGRGI01BTT7U 56  56   -  267   A   -   TTTGC... TTTGC...
        chr22 15255552 15255554 + 49691432  EAYGRGI01BTT7U 71  73   -  267   AG  GA  TTTGC... TTTGC...
        chr22 15255617 15255618 + 49691432  EAYGRGI01BTT7U 136 136  -  267   A   -   TTTGC... TTTGC...
        chr22 15255624 15255625 + 49691432  EAYGRGI01BTT7U 142 142  -  267   A   -   TTTGC... TTTGC...

Sample output for `‑‑format=general:name1,zstart1,end1,strand1,size1,name2,zstart2+,end2+,strand2,size2,text1,text2`.

        chr22 14485616 14485920 + 49691432  EAYGRGI02GQ0SL 0   303  +  303   TGAGA... TGAGA...
        chr22 14731668 14731964 + 49691432  EAYGRGI01EAV19 0   297  -  298   CTTCT... CTTCT...
        chr22 15234302 15234482 + 49691432  EAYGRGI02H5ZGS 0   180  -  180   CGAAT... CGAAT...
        chr22 15238845 15239070 + 49691432  EAYGRGI01BIQCW 0   225  -  225   TGGAA... TGGAA...
        chr22 15255480 15255750 + 49691432  EAYGRGI01BTT7U 0   267  -  267   TTTGC... TTTGC...

(This example aligns reads from the genome of James Watson (available from NCBI’s trace archive by querying for CENTER_NAME = 'CSHL' and CENTER_PROJECT = 'Project Jim') vs. the human reference genome hg18.)

### R Dotplot (alignment output)

This is a home-grown format designed to facilitate plotting the alignment blocks with the R statistical package. Alignments are reduced to a series of gap-free segments, each of which is written in three lines as shown below. Endpoints are origin-one, closed, and alignments on the reverse strand have `<..._query_end>` less than `<..._query_start>` so that R will draw them in the reverse (slope=−1) orientation.

        <target_name>            <query_name_>
        <segment1_target_start>  <segment1_query_start>
        <segment1_target_end>    <segment1_query_end>
        NA                       NA
        <segment2_target_start>  <segment2_query_start>
        <segment2_target_end>    <segment2_query_end>
        NA                       NA
         ...

The file can then be plotted in R with commands like these:

        dots = read.table("your_file",header=T)
        plot(dots,type="l")

When the the query file contains more than one sequence, alignments for each query sequence are written as shown above. This includes a new header line for each query. Unfortunately the simple R commands shown above will not work to plot a file with more than one query.

When the the target file contains more than one sequence, alignments for target sequences are intermixed in the output file. In this case the entire target is treated as a single sequence, and the target positions reported are relative to this concatenated sequence. This can still be plotted using the simple R commands above, but the target sequences will appear as one concatenated sequence in the plot.

### Human-Readable Text (alignment output)

This textual output is intended to be read by people rather than programs. Each alignment block is displayed with gap characters and a row of match/transition characters, and lines are wrapped at a reasonable width to allow printing to paper. The exact format of this output may change in future releases of LASTZ, so programs are better off reading more stable formats like LAV, AXT, or MAF.

### General Output (alignment output)

LASTZ’s General format is a tab-delimited table with one line per alignment block and configurable columns. This format is well-suited for use with spreadsheets and the R statistical package, and for filtering with shell commands.

The syntax for this option is:

        ‑‑format=general[:<fields>]

where `<fields>` is a comma-separated list of field names in any desired order, with no spaces. For example

        ‑‑format=general:nmismatch,name1,strand1,start1,end1,name2,strand2,start2,end2

will report each aligned interval pair and the number of mismatches in the alignment of that pair, like this:

        #nmismatch name1   strand1 start1 end1 name2    strand2 start2 end2
        41         apple8  +       130    930  orange2  -       119    931
        35         apple15 +       113    930  orange3  +       87     909
        52         apple4  +       131    952  orange5  -       111    932
        46         apple7  +       131    930  orange10 +       111    909
        37         apple12 +       131    930  orange11 -       111    909
        38         apple3  +       127    939  orange12 +       107    926

The recognized field names are shown in the table below. Positions (`start` and `end` fields) are counted from the 5' end of the aligning strand, unless otherwise indicated in the table. Please see Interval Coordinates for more information about the position numbering systems used in LASTZ.

If the field list is absent, the following fields are printed, in this order: `score`, `name1`, `strand1`, `size1`, `zstart1`, `end1`, `name2`, `strand2`, `size2`, `zstart2`, `end2`, `identity`, `coverage`.

The option `‑‑format=mapping` is a shortcut for `‑‑format=general` with the following fields: `name1`, `zstart1`, `end1`, `name2`, `strand2`, `zstart2+`, `end2+`, `identity`, `coverage`, `cigarx-`.

Field names are normally included as column headers in the first row of the output, preceded by a `#`. The options `‑‑format=general-[:<fields>]` and `‑‑format=mapping-` suppress column headers. This makes them suitable for concatenating output from multiple runs.

Field | Meaning
`score` | Score of the alignment block. The scale and meaning of this number will vary, depending on the final stage performed and other command-line options.
`name1` | Name of the target sequence.
`number1` | Number of the target sequence within the target file. The first sequence is numbered zero.
`strand1` | Target sequence strand, either "+" or "−".
`size1` | Size of the entire target sequence.
`start1` | Starting position of the alignment block in the target, origin-one.
`zstart1` | Starting position of the alignment block in the target, origin-zero.
`end1` | Ending position of the alignment block in the target, expressed either as origin-one closed or origin-zero half-open (the ending value is the same in both systems).
`length1` | Length of the alignment block in the target (excluding gaps).
`text1` | Aligned characters in the target, including gap characters. `align1` can be used as a synonym for `text1`.
`qalign1` | The target quality sequence (if there is one) correpsonding to aligned characters. Gaps are indicated as a tilde (`~`).
`nucs1` | The entire target sequence, after modifications due to specifier actions such as `subrange` or `softmask`. This is output in order along the target’s forward strand, regardless of the strand of the alignment.
`quals1` | The entire target quality sequence (if there is one), after modifications due to specifier actions such as `subrange`. This is output in order along the target’s forward strand, regardless of the strand of the alignment.
`name2` | Name of the query sequence.
`number2` | Number of the query sequence within the query file. The first sequence is numbered zero.
`strand2` | Query sequence strand, either "+" or "−".
`size2` | Size of the entire query sequence.
`start2` | Starting position of the alignment block in the query, origin-one.
`zstart2` | Starting position of the alignment block in the query, origin-zero.
`end2` | Ending position of the alignment block in the query, expressed either as origin-one closed or origin-zero half-open (the ending value is the same in both systems).
`start2+` | Starting position of the alignment block in the query, counting along the query sequence’s positive strand (regardless of which query strand was aligned), origin-one. Note that if `strand2` is "−", then this is the other end of the block from `start2`.
`zstart2+` | Starting position of the alignment block in the query, counting along the query sequence’s positive strand (regardless of which query strand was aligned), origin-zero. Note that if `strand2` is "−", then this is the other end of the block from `zstart2`.
`end2+` | Ending position of the alignment block in the query, counting along the query sequence’s positive strand (regardless of which query strand was aligned), expressed either as origin-one closed or origin-zero half-open (the ending value is the same in both systems). Note that if `strand2` is "−", then this is the other end of the block from `end2`.
`length2` | Length of the alignment block in the query (excluding gaps).
`text2` | Aligned characters in the query, including gap characters. `align2` can be used as a synonym for `text2`.
`qalign2` | The query quality sequence (if there is one) correpsonding to aligned characters. Gaps are indicated as a tilde (`~`).
`nucs2` | The entire query sequence, after modifications due to specifier actions such as `subrange` or `softmask`. This is output in order along the query’s forward strand, regardless of the strand of the alignment.
`quals2` | The entire query quality sequence (if there is one), after modifications due to specifier actions such as `subrange`. This is output in order along the query’s forward strand, regardless of the strand of the alignment.
`nmatch` | Match count, the number of aligned bases in the block that are matches.
`nmismatch` | Mismatch count, the number of aligned bases in the block that are mismatches (substitutions).
`ncolumn` | Number of columns in the block. This includes matches, mismatches (substitutions), and gaps.
`npair` | Number of aligned bases in the block that are matches or mismatches (substitutions).
`ngap` | Gap count, the number of gaps in the block, counting each run of gapped columns as a single gap.
`cgap` | Gap column count, the number of gaps in the block, counting each gapped column as a separate gap.
`diff` | Differences between what would be written for `text1` and `text2`. Matches are written as `.` (period), transitions as `:` (colon), transversions as `X`, and gaps as `-` (hyphen).
`cigar` | A CIGAR-like representation of the alignment’s path through the DP matrix. This is the short representation, without spaces, described in the Ensembl CIGAR specification. For more information, see the section about CIGAR and its `example`.
`cigarx` | Same as `cigar`, but uses a newer syntax that distinguishes matches from substitutions and omits the run length when it is 1. For more information, see the section about CIGAR and its `example`.
`identity` | Fraction of aligned bases in the block that are matches (see Identity). This is written as two fields. The first field is a fraction, written as `<n>/<d>`. The second field contains the same value, computed as a percentage.
`idfrac` | Fraction of aligned bases in the block that are matches (see Identity), written as a fraction.
`id%` | Fraction of aligned bases in the block that are matches (see Identity), written as a percentage.
`blastid%` | Fraction of the alignment block that is matches, as would be reported by NCBI BLAST. The numerator is the number of matches, and the denominator is the number of alignment columns. The value is written as a percentage but without a percent sign. This is not the same as LASTZ normally reports for identity, since NCBI BLAST includes gaps in the computation.
`continuity` | Rate of non-gaps (non-indels) in the alignment block (see Continuity). This is written as two fields. The first field is a fraction, written as `<n>/<d>`. The second field contains the same value, computed as a percentage.
`confrac` | Rate of non-gaps (non-indels) in the alignment block (see Continuity), written as a fraction.
`con%` | Rate of non-gaps (non-indels) in the alignment block (see Continuity), written as a percentage.
`coverage` | Fraction of the entire input sequence (target or query, whichever is shorter) that is covered by the alignment block (see Coverage). This is written as two fields. The first field is a fraction, written as `<n>/<d>`. The second field contains the same value, computed as a percentage.
`covfrac` | Fraction of the entire input sequence (target or query, whichever is shorter) that is covered by the alignment block (see Coverage), written as a fraction.
`cov%` | Fraction of the entire input sequence (target or query, whichever is shorter) that is covered by the alignment block (see Coverage), written as a percentage.
`diagonal` | The diagonal of the start of the alignment block in the DP matrix, expressed as an identifying number `start1-start2`.
`entropy1` | The entropy of the aligned nucleotides in the target. This represents, in log2, the probability distribution of the nucleotides.
`entropy2` | The entropy of the aligned nucleotides in the query. This represents, in log2, the probability distribution of the nucleotides.
`shingle` | A measurement of the shingle overlap between the target and the query. This is intended for the case where both the target and query are relatively short, and their ends are expected to overlap.
`number` | The alignment number, counted as alignments are written to output. The count begins at one.
`znumber` | The alignment number, counted as alignments are written to output. The count begins at zero.
`chore` | The identifying tag corresponding to the chore that produced the alignment. The tag is defined in the alignment chores file.

### Other Output

LASTZ includes support for other output formats which are intended mainly for the convenience of the developers. If you have specific questions, please contact us.

## Advanced Topics

### Aligning to Whole Genomes

Aligning queries to a whole genome can be accomplished in a single run of `lastz` by using the `multiple` action in the target file’s sequence specifier. This causes `lastz` to load all of the target’s sequences into memory. However, sequence indexing inside `lastz` is limited to 31-bit positions, which limits the overall size of the target to 2 gigabases.

To facilitate larger genomes, an additional executable (`lastz_32`) can be built. The two executables are basically the same; the only difference is that sequence indexing in `lastz` is limited to 31-bit positions, while `lastz_32` uses 32-bit positions. The use of smaller positions in `lastz` reduces memory usage and improves performance, but limits the size of the target sequence to 2 gigabases.

To build the `lastz_32` executable, enter the following commands from bash or a similar command-line shell (Solaris users should substitute `gmake` for `make`). This will build the executable and copy it into your `installDir`.

        cd <somepath>/lastz-distrib-X.XX.XX/src
        make lastz_32
        make install_32

`lastz_32` can then be used as a replacement for `lastz` in any command line, e.g.

        lastz_32 hg18.fa[multiple] galGal3.fa \
          --notransition --step=20 --nogapped \
          --progress=1 \
          --format=maf > hg18_vs_galGal3.maf

Similarly, an experimental executable (`lastz_40`) can be built. This is provided solely on an experimental basis — the intended use case is aligning relatively small queries to a genome larger than 4 gigabases. Users should not expect reasonable runtimes for other uses, and queries larger than 100 kilobases trigger a warning.

### Adjacent Indels

Occasionly the sequences being compared contain unrelated segments of DNA flanked by segments that are related. If the unrelated segments are long enough (and different enough) that two gaps are cheaper than a series of substitutions, the optimal-scoring alignment should contain adjacent indels, like this:

        ...ATAAATTATTATTATTAAATTTTA-------------------CCCCCCCCCCCCCCCCCCTTTTTA...
        ...ATAAATTATTATTATTAAATTTTAGGGGGGGGGGGGGGGGGAG-------------------TTTTA...

However, by default, lastz does not allow an insertion to follow a deletion, or vice versa. So it ends up reporting an alignment like this instead:

        ...ATAAATTATTATTATTAAATTTT------------------ACCCCCCCCCCCCCCCCCCTTTTTA...
        ...ATAAATTATTATTATTAAATTTTAGGGGGGGGGGGGGGGGGA------------------GTTTTA...

The latter alignment doesn't make any sense biologically. However, to maintain backward compatibility with previous versions of LASTZ (and BLASTZ), the default version of LASTZ will produce the latter alignment.

Users that want to allow allow alignments with adjacent indels can build any LASTZ executable with `allowBackToBackGaps` enabled. This is accomplished by adding `allowBackToBackGaps=ON` to the `make` command line, like this:

        make clean
        make lastz_32 allowBackToBackGaps=ON
        make install_32

### Interval Coordinates

The biological research community has established several competing standards describing intervals on a strand of DNA. Different programs often use different standards. Since LASTZ supports several input and output formats, it is inevitable that it uses more than one way of describing an interval. We describe the different conventions here.

For this discussion, suppose we have a 50-nucleotide strand of DNA as follows:

            origin-one, closed: 12345678901234567890123456789012345678901234567890
                                          ↓      ↓
                         5' >>> CGACCTTACGATTACCTACTTAACACGTAAACTGAGGGATCAAAAGGAAA >>> 3'
                                          ↑       ↑
        origin-zero, half-open: 01234567890123456789012345678901234567890123456789

Note that since this is DNA it has 5' and 3' ends; we assume that all input sequences follow the standard practice of listing the bases with the 5' end on the left. Here we've highlighted the subsequence `ATTACCTA` so we can discuss how to describe the interval it occupies. There are two commonly used ways to do this. Both count from 5' to 3' (left to right). One way, origin-one, starts counting from one. The other way, origin-zero, starts counting from zero. So in origin-one, `ATTACCTA` begins at position 11, while in origin-zero it begins at position 10.

To describe the ending position, there are also two commonly used methods. One way is closed, in which the position of the last nucleotide is given. The other is half-open, in which the position following the last nucleotide is given. These are theoretically independent of the conventions for the origin, but in practice only two of the combinations are commonly used: origin-one, closed and origin-zero, half-open. In the former, `ATTACCTA` is said to occupy the interval (11,18), while in the latter it is said to occupy the interval (10,18). Notice that only the first number changes between these two paradigms; the second number stays the same.

Another factor to consider is that DNA is usually double stranded, which would look like this:

            along forward:        12345678901234567890123456789012345678901234567890
                                            ↓      ↓
           forward strand: 5' >>> CGACCTTACGATTACCTACTTAACACGTAAACTGAGGGATCAAAAGGAAA >>> 3'
        complement strand: 3' <<< GCTGGAATGCTAATGGATGAATTGTGCATTTGACTCCCTAGTTTTCCTTT <<< 5'
                                            ↑      ↑
            along reverse:        09876543210987654321098765432109876543210987654321

In some cases it makes sense to refer to the interval along the complement strand. For example, if the above sequence was a query and the target contained `TAGGTAAT`, how should the query position of an alignment of those two be described? One way would be to still refer to the interval along the forward strand (which we also call the plus or positive strand), and just indicate that in fact it was the reverse complement of that interval that aligned. We call this counting along the forward strand. Another way is to count from the other end, from the 5' end of the complement strand (which we also call the reverse, minus or negative strand). We call this counting along the reverse strand, and for clarity we might add "from its 5' end". In this example, if we were using origin-one, closed counting, we would say that `TAGGTAAT` occurs at (33,40) along the reverse strand. Unless noted otherwise (e.g. for the R Dotplot output format), when counting along the forward or reverse strand LASTZ swaps the interval’s endpoints if necessary, so the position called `start` is numerically ≤ the position called `end`. This is a common convention, but there are other programs that leave them unswapped.

Note that when counting positions all characters in the sequence are counted, including runs of `N`s or `X`s and even invalid characters. This is important so that other programs can use the reported positions to index directly into the original sequences.

### Non-ACGT Characters, Splicing, and Separation

The handling of characters other than `A`, `C`, `G`, and `T` in sequences that are supposed to represent DNA is problematic. In ordinary (non-quantum) DNA sequences, LASTZ currently supports two of these, `N` and `X`. They can either be present in the original input file (except that the Nib and 2Bit formats are incapable of containing `X`s), or added by using an `xmask` or `nmask` action in the sequence specifier. LASTZ can also be configured to tolerate the other IUPAC-IUB ambiguity codes (`B, D, H, K, M, R, S, V, W,` and `Y`), and to recognize a special user-specified separator character.

Many database sequences contain `N`s to represent bases for which the actual nucleotide is not known (at least, not known with any level of confidence). `N`s (or better, `X`s) can also be used to mask out regions that have previously been identified as being of no interest, and therefore should not be aligned. And unfortunately, there is also a tradition of using strings of `X`s or `N`s to splice together multiple sequences to gain efficiency when dealing with programs that were limited to operating on a single sequence.

Although splicing was useful in BLASTZ, it is no longer needed for LASTZ. Since LASTZ can handle multiple target sequences (via the `multiple` action in the target file’s sequence specifier), it is preferred that users not resort to splicing. If splicing is necessary, the preferred method is to specify a separator character to tell LASTZ explicitely where the splices have occurred.

Replacing BLASTZ with LASTZ in an existing pipeline may still involve spliced sequences, so LASTZ’s default interpretation of non-ACGT characters is the same as BLASTZ’s: `X`s are excluded from the alignment seeding stage, and are so severely penalized by alignment scoring that they will not normally appear in any alignment. `N`s are also excluded from seeding, and are penalized about the same as a transversion mismatch. Specifically, any substitution with `X` is scored as −1000, and any substitution with anything else (other than `A`, `C`, `G`, or `T`) is scored as −100. Note that you have to put "enough" `X`s or `N`s between the sequences so that no alignment block will cross the splice. This can be tricky, since gap scoring is only dependent on the length of the gap and not on the characters in the gap. So if a gap the same length as the splice is not penalized more than the y-drop setting, the alignment may hop the splice. As a rough guideline, a splice length of 50 is usually enough with the default settings, but this is not guaranteed.

This default treatment of non-ACGT characters also works well when `X`s or `N`s are used to mask out regions that should not be aligned. However, it is inappropriate when the sequences contain `N`s to represent ambiguous bases. To handle this case, LASTZ provides the `‑‑ambiguous=n` option, which causes substitutions with `N` to be scored as zero. Additionally, the `‑‑ambiguous=iupac` option causes the other IUPAC-IUB ambiguity codes (`B, D, H, K, M, R, S, V, W,` and `Y`) to be treated this same as an ambiguous `N`. The two `‑‑ambiguous` options also allow you to specify rewards and penalties for matches and mismatches involving ambiguous characters.

In either case, non-ACGT characters are ignored during the seeding stage. Only seed words that consist entirely of `A`, `C`, `G`, and/or `T` are involved in seeding, even if the non-ACGT characters occur in "don't-care" positions in the seed pattern.

The score values described above can be changed if a scoring file is specified. The −1000 score is called `bad_score` and the −100 score is called `fill_score`. Further, which character is considered "bad" (by default this is `X`) can also be specified in the scoring file, and can actually be different between the target and query. Throughout this document, when we refer to the character `X` appearing in a DNA sequence, we generally mean the character specified as "bad", which defaults to `X`.

Splicing, or more correctly separation, can also be accomplished by placing a specific character between subsequences, then using the `separator=<character>` action. LASTZ will then break the sequence into the prescribed subsequences and prevent any alignment from crossing the boundaries.

Quantum DNA sequences are different: they use an arbitrary, user-defined alphabet of symbols, so the above-mentioned special treatments for `N` and `X` do not apply. The default "bad" character for quantum sequences is the null byte (`00` hexadecimal), which is not even allowed in the sequence; however it can be changed to one of the valid alphabet symbols via the scoring file. There is no analog of ambiguous `N`s for quantum sequences, as typically every symbol has some level of ambiguity.

### Sequence Name Mangling

Often the names in the input sequence files are inconvenient for downstream processing, or create problems with certain output formats. This is further complicated by the fact that some input formats (most notably Nib) do not contain sequence names, so in those cases a name must be derived from the filename. LASTZ provides several choices for naming the input sequences. These alternatives are mutually exclusive; only one can be used at a time for a particular input file.

Internally, LASTZ handles the naming task in two phases. First, it creates a full header for the sequence. If the input format provides a name or header, that becomes the full header. Otherwise, the full header is constructed from the file name.

In the second phase, LASTZ shortens the full header to a nickname. If the full header starts with a file name, any path prefix is removed, and commonly-used file extension suffixes are also removed (`.fa`, `.fasta`, `.nib`, `.2bit`). Then by default, LASTZ uses the first word (composed of characters other than whitespace, vertical bar, or colon) of the remaining string as the sequence name. Thus a FASTA header like "`> ~someuser/human/hg18/chr1.fa Human Chromosome 1`" is shortened to simply `chr1`.

The actions `nameparse=darkspace` and `nameparse=alphanum` in the sequence specifier change how the first word is determined. `darkspace` (i.e., "non-whitespace") narrows the set of terminating characters to allow vertical bars and colons to appear in the word, while `alphanum` widens it so the word is restricted to only alphabetic, numeric, and underscore characters. Path prefixes and file extensions are still removed.

The default shortening is often adequate. For example, consider the following FASTA file. By default, the names will be `000007_3133_3729` and `000015_3231_1315`.

        >000007_3133_3729 length=142 uaccno=FX9DQEU13H5YZN
        ACCCGAAAGAGAAACAGCTTCCCCCCCTGTCCCGAGGGATATCAAGTAGTTTGTTGGCTA
        GGCTGATATTGGGGCCTTCCGCTAGAGTCGGCGCCCGCGCCTACGAGTCCCCCCCACCCC
        CCACCCCCACAGCGGGTTATCC
        >000015_3231_1315 length=190 uaccno=FX9DQEU13HUTXE
        TTGTTGAGTCGGATGAGAATAGCAAGTGCAGTCAACGGCAATGTGCTGGGTTAGTACAAC
         ...

However, the user may find it more convenient to use the accession numbers. To accomplish this, she can use the `nameparse=tag:uaccno=` action. LASTZ will look for the tag string `uaccno=` in each header and read the name from the characters that follow it, up to the first character that is not alphabetic, numeric, or an underscore. In this case the sequence names would be `FX9DQEU13H5YZN` and `FX9DQEU13HUTXE`. If the tag string is not found in the full header for a particular sequence, the default shortening is used instead.

Now consider this FASTA file:

        >gi|197102135|ref|NM_001133512.1| Pongo abelii ...
        GCGCGCGTCTCCGTCAGTGTACCTTCTAGTCCCGCCATGGCCGCTCTCACCCGGGACCCC
        CAGTTCCAGAAGCTGCAGCAATGGTACCGCGAGCACGGCTCCGAGCTGAACCTGCGCCGC
         ...
        >gi|169213872|ref|XM_001716177.1| PREDICTED: Homo sapiens ...
        ATGTCTGAGGAGGTAGGATTTGATGCAGGAGGGAGGATCTGGTGCACTTATAAGGATCTG
        GGTCTGTCAGTGTCAGAGAAGGTAGGATCTGGCCCTGGTATGAGGATCTGGATCTGTCAG
         ...
        >gi|34784771|gb|BC006342.2| Homo sapiens ...
        GGGTGGGAGGACGCTACTCGCTGTGGTCGGCCATCGGACTCTCCATTGCCCTGCACGTGG
        GTTTTGACAACTTCGAGCAGCTGCTCTCGGGGGCTCACTGGATGGACCAGCACTTCCGCA
         ...

In this case the default action does not do what we want (all sequences would be named `gi`). The action `nameparse="tag:gi|"` gives us the names `197102135`, `169213872`, and `34784771`. (Note the quotes; this is necessary to prevent the command-line shell from interpreting `|` as a pipe character.) Observe that a tag of `ref|` will not work, because the third sequence would need `gb|` instead.

Sometimes it is more convenient just to assign a specific name. This can be done with the `nickname=<name>` action. For example, using the target and query file specifiers `~someuser/human/hg18/chr1.nib[nickname=human]` and `~someuser/human/ponAbe2/chr1.nib[nickname=orang]`, the output will show the sequences as `human` and `orang` rather than calling them both `chr1`. If `<name>` contains the substring `{number}`, the nickname will contain the number of the sequence within the file. This is particularly useful when there is more than one sequence in the file.

If you want to do away with name mangling entirely, you can use the action `nameparse=full`. This uses the full header as the sequence name. But note that if it contains spaces, the resulting alignment files may not be readable by downstream tools.

The above discussion applies to ordinary DNA sequences in FASTA, Nib, or 2Bit format. HSX index files are handled differently: by default LASTZ uses the name from the index as-is, without shortening it, and the various `nameparse` actions are not allowed. The `nickname` action can be used, but is generally not necessary since you can store the names you want directly in the index.

Note that if the `subset=<names_file>` action is used, the names in the `<names_file>` must match the mangled (or indexed) names.

For FASTA files, more complicated name mangling can be performed using standard Unix command-line tools. In the second example above, we could pipe the input through `sed` a couple times to shorten each name to the NCBI accession numbers `NM_001133512.1`, `XM_001716177.1`, and `BC006342.2`.

        cat query_file.fa \
          | sed "s/>.*ref\|/>/g" \
          | sed "s/>.*gb\|/>/g" \
          | lastz target /dev/stdin

### Seed Patterns

Seeds are short near-matches between the target and query sequences, where "short" typically means less than 20 bp. Early alignment programs used exact matches (e.g. of length 12) as seeds, but spaced seeds can improve sensitivity when the sequences are diverged.

A spaced seed pattern is a list of positions, in a short word, where a seed may contain mismatches. For example, consider the seed pattern `1100101111`. A `1` indicates a match is required in this position, and a `0` indicates a mismatch is allowed (effectively it is a "don't care" position). As the example below shows, using this seed pattern, the seed word `GTAGCTTCAC` hits twice in the sequence `ACGTGACATCACACATGGCGACGTCGCTTCACTGG`.

            target:  ACGTGACATCACACATGGCGACGTCGCTTCACTGG
        (mis)match:    ||XX|X||||          ||X|||||||
             query:    GTAGCTTCAC          GTAGCTTCAC
           pattern:    1100101111          1100101111

Spaced seeds have been shown to be more sensitive than exact match seeds, with little change in specificity. This is most advantageous when the sequences have lower similarity, such as human vs. mouse or chicken. Which seed pattern is best depends on the sequences being compared. See [Buhler 2003] for a discussion of spaced seeds and how to design them.

LASTZ’s seeding options give the “user” many choices. The intent is that these will be selected by some program (hence the quote marks around “user”), but they are available from the command line for anyone.

#### N-mer match:

A space-free seed can be specified by the length of the N-mer match required.

        --seed=match<length>

#### General seed patterns:

Any spaced seed pattern can be specified. The pattern is a string of `1`s, `0`s, and `T`s, where a `1` indicates that a match is required in that position, a `0` indicates that a mismatch is allowed, and a `T` indicates that a mismatch is allowed only if it is a transition (A↔G or C↔T).

        --seed=<pattern>

The default seed is `‑‑seed=1110100110010101111`, which is the same 12-of-19 seed used as the default in BLASTZ.

#### Half-weight seed patterns:

If a seed pattern consists of only `0`s and `T`s, it is implemented internally as a half-weight seed, which uses much less memory (the same amount as a normal seed pattern half as long). Additionally, `‑‑seed=half<length>` can be used as shorthand to specify a space-free half-weight seed (i.e., all `T`s).

#### Single, double, or no transitions:

By default, one match position (a `1` in a spaced seed, or any position in an N-mer match) is allowed to be a transition instead of a true match. `‑‑notransition` disables this. Alternatively, `‑‑transition=2` allows any two match positions to be transitions.

#### Filtering on transversions and matches:

The `‑‑filter` option imposes additional requirements on the number of transversions and matches in a valid seed. This is especially useful in conjunction with half-weight patterns. For example,

        --seed=TTT0T00TT00T0T0TTTT --filter=2,15

specifies the same pattern as the default seed, but allows the twelve `T` positions to be matches or transitions, requires at least fifteen matches total (among the 19 positions), and allows at most two transversions. Note that the transversions can only occur in the `0` positions, since the `T` positions allow only matches or transitions. And although there are seven `0` positions, five of them must contain matches or transitions since only two transversions are allowed.

#### Twin hit seeds:

The sensitivity of the seed can be decreased by ignoring seeds that don't have a second hit nearby, i.e. by requiring two seeds on the same diagonal.

        --twins=[<minsep>..]<maxsep>

The distance between the hits (the number of bases between the end of the first hit and the beginning of the second) must be at least `<minsep>` but not more than `<maxsep>`. If `<minsep>` is omitted, zero is used (which means the twin seeds may be adjacent but not overlap). Negative values can be used; for example `‑‑twins=‑5..10` means the twins can overlap by as much as 5 bases or can have as much as 10 bases between them.

### Any-or-None Alignment

Sometimes, the only answer you want from an aligner is whether a query has any strong alignments to the target or not. For example, you may want to know which reads in a sequencing run have no alignment with a reference genome. In this case, if a read aligns to a thousand different places on a particular chromosome, you aren't interested in learning where — all you want to know is whether it aligned or not.

The `‑‑anyornone` option is designed for such cases, and can significantly improve alignment speed. Once any qualifying alignment has been found, processing for the current query is halted. The alignment is reported to the output, and then we immediately begin processing the next query. A qualifying alignment is one that would normally be output given the other parameter settings; for example it satisfies the scoring thresholds (`‑‑hspthresh` and/or `‑‑gappedthresh`) and any back-end filters.

To get a list of reads that have at least one "good" alignment with a reference sequence, you could do something like this:

        lastz <reference> <reads> --anyornone  \
          --step=10 --seed=match12 --notransition --exact=20 --noytrim \
          --match=1,5 --ambiguous=n \
          --filter=coverage:90 --filter=identity:95 \
          --format=general:name2

This option slightly changes the usual processing order described in the Overview. Instead of performing gap-free extension on all seeds, collecting them into a list of HSPs, and then performing gapped extension, each HSP is gap-extended and back-end filtered immediately. This avoids wasted work to perform complete early stage processing on hits that will just be abandoned as soon as the first qualifying alignment is found.

### Y-drop Mismatch Shadow

The default configuration of gapped extension in LASTZ is to end the alignment where the score would be the highest. This means that any prefix or suffix of the alignment will have a non-negative score. While this is appropriate for alignments that lie somewhere in the middle of two long sequences, it is not desirable when an alignment is near the end of one or both sequences, which happens quite often when aligning short reads.

Consider the following alignment of a 50-base query to a chromosome target, and suppose we are using `‑‑match=1,5`, `‑‑gap=6,1`, `‑‑filter=identity:97`, and `‑‑filter=coverage:95`. The entire alignment as shown has 97.9% identity (46/47) and 100% coverage. However, the first five bases (`AGAAC` vs. `AGAAG`) have a negative score: four matches at +1 each and one mismatch at −5 gives a score of −1 for this prefix. The highest scoring alignment is from positions 6 through 50, for a score of 33 (the entire alignment scores only 32). If we stop the alignment at the highest score, coverage drops to 90%, and the alignment is discarded. The overall result is that we will discard reads that we don't want to, and we will see a bias against mismatches near the ends of reads. (Note that this anomaly arises because the alignment is terminated abruptly by the end of the sequence rather than normally by a low-scoring region; also the `‑‑filter=coverage` option is more commonly used with short reads than with longer sequences.)

        target:  ... CTTAGAACGGTAGATACTTGTATAAT---CGAGGGGGTTATTTTGTACAAATGACT ...
                        ||||X||||||||||||||||||   ||||||||||||||||||||||||
         query:         AGAAGGGTAGATACTTGTATAATCAACGAGGGGGTTATTTTGTACAAATG
                             ↑                                           ↑
                        12345678901234567890123456789012345678901234567890

To avoid this behavior, use the `‑‑noytrim` option when aligning short reads. This causes LASTZ to refrain from trimming such alignments back to the highest-scoring location. Specifically, if the gapped extension process encounters the end of the sequence, it will keep that as the end of the alignment. In this case a negatively-scoring prefix or suffix will be kept as long as it does not score worse than the `‑‑ydrop` value.

### Shingle Overlap

In some applications, e.g. when assembling reads into contigs, we want to determine how sequence ends overlap each other. For example, in case 1 below, the starting portion of the query overlaps the ending portion of the target by 30 bases, and both sequences extend beyond each other in opposite directions. We call this situation "shingling" (like shingles on a rooftop), and the `shingle` field of the General output format provides a measurement of it. A positive value indicates that the starting portion of the query overlaps the ending portion of the target (case 1), while a negative value indicates the roles are reversed (case 2). If neither of these cases occurs (e.g. if either sequence fails to extend beyond the other), an `NA` is reported.

Case 1 (shingle = +30):

                                                        target_end
                               3         2         1        ↓
                               098765432109876543210987654321
        target:  ... GACGGCGGCTAACACATTGTGTTGXACGTACCATAACCAA
                               ||||||X|||||||||XX||X||||||
         query:                AACACAGTGTGTTGCAACTATCATAACATTAAACTTTAGA ...
                               123456789012345678901234567890
                               ↑        1         2         3
                          query_start

Case 2 (shingle = −30):

                         target_start
                               ↓        1         2         3
                               123456789012345678901234567890
        target:                TCCCTAATAAATCTTAAGTGCGATCCGCAGCGAGGTGTAC ...
                                  ||||X|||||||||X||||||||X||
         query:  ... TGGCGCCTGTAGTCTAAGAAATCTTAATTGCGATCCACAC
                               098765432109876543210987654321
                               3         2         1        ↑
                                                        query_end

Note that the value reported has no relation to the number of bases that align in that region, nor is it an indication that the alignment extends all the way to the start or end of the sequences. The shingle value is just evidence that the proper registration of the two reads is to overlap them by the given value — information that an assembler might use in assembling those reads into a contig.

### Using Target Capsule Files

Target capsule files are provided to improve run-time memory utilization when multiple CPU cores on the same computer are running LASTZ with the same target sequence. They permit the lion’s share of the large internal data structures to be shared between the processes. This allows more copies of LASTZ to be run simultaneously with less physical memory, which can improve the throughput, for example, when mapping a large set of reads to a single (large) reference sequence.

To create a capsule file, use a command like this:

        lastz <target> --writecapsule=<capsule_file> [<seeding_options>]

Applicable seeding options are `‑‑seed`, `‑‑step`, `‑‑maxwordcount`, and `‑‑word`.

To use the capsule file, run LASTZ like this:

        lastz --targetcapsule=<capsule_file> <query> [<other_options>]

No additional effort on the part of the user is required to handle sharing of the capsule data between separate runs. Nearly all options are allowed; however the seeding options `‑‑seed`, `‑‑step`, `‑‑maxwordcount`, and `‑‑word` are not allowed, since these (or their byproducts) are already stored in the capsule file. Further, `‑‑masking` is not allowed, because it would require modifying both the target sequence and the target seed word position table, which are contained in the capsule.

Internally LASTZ asks the operating system to directly map the capsule file into the running program’s memory space in a read-only fashion. Multiple running instances can map the same file; each instance will have its own virtual addresses for the capsule data, but the physical memory is shared. There is no requirement for more than one instance to actually use the capsule simultaneously. Running a single copy of `lastz` with `‑‑targetcapsule` will work fine, and in fact there may be a small speed improvement compared to running the same alignment without a capsule.

The downside of this technique is that the capsule files are very large and are also machine-dependent. For example, the file for human chromosome 1 is about 1.4 Gb. Note that attempts to run a capsule built on a mismatched computer are detected and rejected.

### Inferring Score Sets

Scoring inference is an automated method for determining appropriate substitution scores and/or gap penalties directly from the sequences being aligned. The resulting scoring parameters can be saved to a file and/or used immediately to align the sequences. Generally these depend mostly on the species rather than particular regions, so once a suitable scoring set has been obtained for a pair of species, the inference does not need to be performed for each alignment run. In this section we give a brief overview of the inference process; see [Harris 2007] for a more detailed description.

Inference is achieved by computing the probability of each of the 18 different alignment events (gap open, gap extend, and 16 substitutions). These probabilities are estimated from alignments of the sequences. Of course, at first we don't have alignments, so we start by using a generic scoring set to create alignments, infer scores from those, then realign, and so on, until the scores stabilize or "converge". Ungapped alignments are performed until the substitution scores converge, then gapped alignments are performed (holding the substitution scores constant) until the gap penalties converge.

To have LASTZ infer scoring parameters, use a suitably enabled build of LASTZ (see below), and specify the `‑‑infer` or `‑‑inferonly` options. (The latter will stop after inferring the parameters, without performing the final alignment.) Settings for the inference process can be specified in a control file included with these options.

The `‑‑infscores` option causes the inferred scoring parameters to be written out to a separate file. If no `<output_file>` is specified, it is written to the header of the alignment output file, as a comment. As a last resort, if no alignment is performed the scoring set is written to `stdout`. The parameters are written in the same format used to input scoring sets.

Usually it is undesirable to use all alignment blocks for inference. Blocks with a high substitution rate (low identity) are likely to be false positives. On the other hand, blocks with few substitutions (high identity) will be found regardless of what scoring parameters are used. Thus it is desirable to base the inference only on statistics from a mid-range of identity. By default the middle 50% is used (that is, the 25th through 75th percentile from the identity distribution), but this can be changed in the control file.

#### Special Builds Required:

Since the inference is an iterated process, greater accuracy can be achieved by using the floating-point version of LASTZ (`lastz_D`). Moreover, the technique used to infer gap penalties has not yet been shown to select good values, so the author recommends that users only employ inference for substitution scores. To encourage these recommendations, the scoring inference code is blocked from operation in the integer scoring version of LASTZ (`lastz`), and gap penalty inference is blocked in both versions. Special build options are available to defeat the blocks; contact the author if you are interested.

### Dynamic Programming Matrix

- Dynamic programming in general is a time-saving algorithm for computing values that can be expressed via a recurrence relation [Bellman 1957].
- It has long been used for affine gap alignments of DNA and protein sequences; see e.g. [Gusfield 1997].
- It uses a matrix of sequence positions to store partial results; early cells are used to compute later ones to avoid redundant work.
- Even for stages that do not involve gaps and do not actually use a DP algorithm, the matrix is helpful as a conceptual tool because of its strong correspondence with the dot-plot paradigm for visualizing sequence alignments.
- Here we use the convention of representing the target sequence from left to right along the horizontal axis (columns of the matrix), and the query sequence from bottom to top along the vertical axis (rows of the matrix); see e.g. Figure 5(a) for an example.
- Gap-free alignment segments lie along diagonals of the matrix/dotplot, in the forward (slope=+1) or reverse (slope=−1) orientation; the latter typically indicates an alignment on the reverse strand.
- Gaps bump the alignment to a different diagonal, since there is a progression in one sequence but not in the other; this has the effect of making gapped alignments look like diagonal-trending squiggly lines when drawn at low resolution.
- Diagonals are characterized by a constant difference between the target and query positions of their cells (or for a reverse diagonal, a constant sum).
- This matrix is not to be confused with the substitution scoring matrix, whose rows and columns correspond to characters rather than to sequence positions.

### Filtering With Shell Commands

Though LASTZ provides several filtering options (e.g. `‑‑filter=identity`, `‑‑filter=continuity`, `‑‑filter=coverage`, `‑‑filter=nmatch`, `‑‑filter=nmismatch`, `‑‑filter=ngap` and `‑‑filter=cgap`), sometimes these are not sufficient for the task at hand. But in many cases it is still possible to perform the desired filtering by using the `‑‑format=general` option in conjunction with a simple awk, perl, or python script. Here we show one such example, using awk.

Suppose we want to filter alignments by length, discarding anything shorter than 500 bp, and that we need AXT output for downstream processing. We can have LASTZ output whatever columns are necessary to reproduce AXT and use awk to perform the filtering and reconstruct an AXT file.

Looking at the UCSC AXT specification, the corresponding --format=general fields are shown in the table below. Note that when determining which fields are needed for a given format, care has to be taken to make sure to get the correct start and end fields. Different formats count from zero instead of one, and some count reverse-strand positions along the plus strand. The interval coordinates section provides more detail about possible numbering schemes.

AXT field | field for `‑‑format=general`
Alignment number | (none)
Chromosome (primary organism) | `name1`
Alignment start (primary organism) | `start1`
Alignment end (primary organism) | `end1`
Chromosome (aligning organism) | `name2`
Alignment start (aligning organism) | `start2`
Alignment end (aligning organism) | `end2`
Strand (aligning organism) | `strand2`
Blastz score | `score`
Sequence line (primary assembly) | `text1`
Sequence line (aligning assembly) | `text2`

Then we can perform our filtered alignment with a series of commands like this:

      lastz target.fa query.fa \
         --format=general:name1,start1,end1,name2,start2,end2,strand2,score,text1,text2 \
       | grep -v "^#" \
       | awk '{ if ($3-$2+1 >= 500) print $0 }' \
       | awk 'BEGIN { n=-1;} { print ++n,$1,$2,$3,$4,$5,$6,$7,$8; print $9; print $10; print ""; }' \
       > filtered.axt

The grep command discards the line containing column headers.

The first awk command computes the alignment length in the target, and if it is at least 500, copies the line to the output. `$3` is `end1` and `$2` is `start1`. Since these represent a closed interval, we have to add 1 to get the length. `$0` represents the entire input line.

The second awk command converts the alignment from a single line into four lines required for AXT. We use an awk counter, `n`, to create the alignment number field. The other fields are copied from the fields output by LASTZ.

### Self-Masking a Sequence

For many alignment problems it is desirable to ignore alignments that consist soley of genomic repeats. For this reason, most finished genomic assemblies are soft-masked — bases that are part of identified repeats are in lowercase. LASTZ’s seeding stage avoids seed hits in lowercase, and thereby avoids finding alignments that are solely repeats.

With the wider availability of less-expensive DNA sequencing and custom assemblies, it is more common for users to have unannotated sequences. The following describes how LASTZ can be used to crudely identify duplications and soft-mask the original sequence. This process is called self-masking.

The self-masking process works by looking for alignments of the sequence with itself, and makes use of the dynamic masking feature to reduce computational time. The sequence is split into overlapping fragments, on the fly, which are then aligned against the entire sequence. As duplications are discovered they are marked as such and removed from the seeding process.

A command to perform self-masking would look like this, where critter.fa contains the sequence to be masked.

      cat critter.fa \
        | ../tools/fasta_fragments.py --fragment=200 --step=100 \
        | lastz critter.fa[multiple,unmask,nameparse=darkspace] /dev/stdin --masking=3 \
            --progress+masking=10K \
            --format=none --outputmasking+:soft=critter.masking.dat \
            --notransition

In that command, lastz is given the whole “critter” as its target sequence, and overlapping 200bp fragments of the critter as the queries.

The `multiple` action tells lastz to allow more than one sequence in the file, and the `unmask` action tells lastz to ignore any softmasking that may be present in the file. (If your sequence already has had some masking performed, and you want to keep that, omit `unmask`.) The `nameparse=darkspace` action tells lastz to extract the first non-whitespace string from the sequence header line. This is necessary to ensure that the final step (`fasta_softmask_intervals`) will see the same sequence names in the masked intervals file as those in the sequence file.

The `‑‑masking=3` option enables dynamic masking, which will mark any reference base appearing in 3 or more alignments. Since the fragments overlap by a factor of two, we expect every base will appear in two trivial alignments. Any more than that would be caused by a duplication elsewhere.

The `‑‑progress+masking` option causes lastz to give you a progress report after every 10 thousand fragments. These reports come to the console (stderr) and look like this:

        (16.933s) processing query 50,001: critter_21299501, masked 8,920,893/51,304,566 (17.4%)

The `‑‑format=none` option inhibits the normal alignment output and `‑‑format=outputmasking+:soft` tells lastz to write the final masked intervals to a file.

The final line (`‑‑notransition` in this example) is whatever alignment scoring parameters you want to use. What is appropriate will depend on the level of divergence you want to allow in the masked duplications.

The command to apply the masking intervals to the fasta file will look like this:

      cat critter.fa \
        | ../tools/fasta_softmask_intervals.py --origin=1 critter.masking.dat \
        > critter.softmasked.fa

### Aligning Many Subintervals

There are many occasions when you have a general idea of where the alignments you are interested in are, and it seems computationally wasteful to align entire sequences just to find a relatively few alignments. For instance, you may have identified some alignments using fast, high sensitivity settings and now want to look for alignments with higher divergence in the remaining regions. Or you may have previously found alignments but did not collect all the fields you needed. Or perhaps you used some tool other than LASTZ to identify regions where you want to focus your search. Or you may have gapped alignments from some other tool, and want to compare them to LASTZ's alignments in the same subsequences.

There are many ways to solve such a problem, and LASTZ provides several options to support these needs. Here we describe and critique several different approaches.

Sequence masking. LASTZ can use masking to eliminate the possibility of alignments in (or not in) a given list of intervals. So we can create two files, containing the desired intervals in the target and query, then run one LASTZ job.

The disadvantage of this solution is that you may get alignments between unintended interval pairs (for example, an alignment between the first target interval and the fifth query interval). Some post-proceesing would be necessary to eliminate these. Moreover, LASTZ will be spending a lot of its time looking for alignments in those unintended interval pairs.

Separate files. The simplest solution, conceptually, is to preprocess the sequences to extract the intervals of interest into separate files, then run each pair of files as a separate LASTZ job.

The disadvantages of this solution are numerous. There is extra I/O involved in splitting the files, and extra overhead in repeatedly launching LASTZ. Further, depending on your needs, post-processing may be necessary to map alignment positions back to the original sequences.

Subranges and subsets. The separate files solution can be improved upon by letting LASTZ mimic the file splitting, internally. This can be accomplished with the subrange and subset actions, while still running each as a separate lastz job.

This improves upon external file separation by eliminating some I/O, and eliminating the need to post-process to map positions. However, it still suffers the extra overhead of repeatedly launching LASTZ.

Alignment chores. Another solution is to use an alignment chores file (specified with the `‑‑chores=<file>` option). The chores file corresponds directly to the interval pairs of interest. Complete alignment is performed over the regions defined by each pair (subject to whatever other options have been set), and is blocked from extending beyond the region.

There is little downside to this solution. The reported results will be the same as for the post-processed separate files solution, or subrange/subset solution (but with minor variations such as shifting of equally-scoring gap placements). There is some computational waste in the chores solution, but this is much less costly than the repeated launching.

In most cases, a chores file will be preferred over an anchors file.

Anchor segments. Another solution is to use an anchor segments file (specified with the `‑‑segments=<file>` option). The anchors file does not correspond directly to the interval pairs of interest. Instead, you will need to have same-length intervals in target and query. Typically this will be a single point somewhere in the region. Alignment is anchored at this point. Gapped alignment is performed in both directions from that point, and is not restricted to the region.

The main disadvantage of this solution is lack of versatility. It is most appropriate when used in conjunction with an external anchor-identifying method.

It can also be useful in cases where you want to run ungapped alignment with a different scoring scheme than for gapped alignment. An ungapped run of LASTZ creates the anchors (segments) file, and a second run uses those as anchors for ungapped alignment with a different scoring scheme.

## Differences from BLASTZ

- BLASTZ had a "short-by-two" error, which has been corrected in LASTZ. In many cases, BLASTZ shortened alignments by two bases on either or both ends.

- BLASTZ had a problem with premature alignment termination; this has been corrected in LASTZ.

- BLASTZ used the ydrop value from the main alignment as the xdrop value for interpolation; this has been corrected in LASTZ.

- BLASTZ had a problem when ydrop is less than the penalty for a one-base gap; this has been corrected in LASTZ.

- BLASTZ chaining had a problem that caused it to discard very high-scoring HSPs; this has been corrected in LASTZ.

- The handling of ties in the DP matrix was unspecified in BLASTZ. This has changed in LASTZ, which specifically prefers a longer alignment to a shorter alignment with the same score. This change reflects the use of LASTZ to align short reads, and desire to align as much of the read as possible.

- The handling of bounding alignments in the DP matrix is different in LASTZ than in BLASTZ. This is discussed in Bounding Alignments in the DP Matrix. The `‑‑allgappedbounds` option can be used to revert to the bounding criteria used in BLASTZ.

- The handling of amibiguous nucleotides has been clarified in LASTZ, and in some cases the default behavior is different than in BLASTZ. By default, BLASTZ allowed IUPAC-IUB ambiguity codes (`B, D, H, K, M, R, S, V, W,` and `Y`) in fasta sequences but was unclear about how these were scored. Since we feel the user should be aware of how these bases are treated, LASTZ rejects them by default. The `‑‑ambiguous=iupac` option permits them but treats them the same as an ambiguous `N`. This is discussed in Non-ACGT Characters.

- LASTZ can produce a variety of alignment output formats such as AXT, MAF, and human-readable text, as well as BLASTZ’s LAV format.

- LASTZ can take the guesswork out of selecting alignment scoring parameters by inferring them for you, based on its analysis of the input sequences.

- LASTZ provides a large variety of seeding options.

### Bounding Alignments in the DP Matrix

During the gapped extension stage, LASTZ processes the anchors in order of score (highest scoring anchor is extended first, and so on). As anchors are extended, a list of bounding alignments is constructed. These correspond to paths in the DP matrix. Bounding alignments created for higher-scoring anchors are used to bound the possible DP paths that lower-scoring anchors can take. This prevents alignments from crossing each other.

In BLASTZ, every gapped extension became a bound, and this was originally the default behavior in LASTZ, through release 1.1.52. However, this caused LASTZ to miss some alignments which it should have found. The failure case occured as follows. A high-scoring anchor is extended but fails to meet the score threshold. But it gets added as a bound. Then the extension of a lower-scoring anchor is prevented from crossing or intersecting with that path, and it too gets discarded even though it might score highly enough. This could occur, for example, when two extensions would (in the absence of each other) share the same tail, and the higher-scoring of the two has a lower-scoring anchor.

The correction for this is to only use alignments as bounds if they satisfy the score threshold. This corrected behavior is now the default in LASTZ (as of release 1.02.00). The `‑‑allgappedbounds` option can be used to revert to the bounding criteria used in BLASTZ.

## Change History

Release | Date | Changes
--- | --- | ---
1.0.1 | Jul/28/2008 | Initial release.
1.0.5 | Aug/2/2008 | Fixed a bug that in some cases caused a bus error when interpolated alignments (e.g. `‑‑inner=`…) were used with multiple queries.
|  | Added `xmask=<file>` and `nmask=<file>` file masking actions.
1.0.21 | Sep/9/2008 | Fixed a bug involving the default value for `‑‑gappedthresh` (a.k.a. `L`) when `‑‑exact` is used. The bug caused the gapped threshold to be inordinately low, allowing undesirable alignment blocks to make it to the output file.
|  | Fixed a bug whereby Xs and Ns were treated as desirable substitutions when unit scores (e.g. `‑‑match=`…) were used.
|  | Re-implemented `‑‑twins=`…. The previous implementation improperly truncated the left-extension of HSPs. The new implementation is slower and uses more memory.

Added `‑‑census=<file>`. The census counts the number of times each base in the target sequence is part of an alignment block. Previously, `‑‑census` produced a census only if the output format was LAV (the census is a special stanza in a LAV file). Otherwise the option was ignored. Now, if a file is specified a census is written to that file. The format of lines in the census is `<name> <position> <count>`. The position is one-based, and the count is limited to 255.

In situtations where 255 is too limiting, `‑‑census16=<file>` or `‑‑census32=<file>` can be used, with limits of about 65 thousand and 4 billion, respectively. Note that these will respectively double and quadruple the amount of memory used for the census. The default census uses one byte per target sequence location.

|  | Added `‑‑format=<differences>`, to support Galaxy. All differences (gaps and runs of mismatches) are reported, one per line.
|  | Added `‑‑anchors=<file>` (eventually this was renamed to `‑‑segments=<file>`), giving the user the ability to bypass the seeding and gap-free extension stages.
|  | Changed default gap penalties for unit scores (e.g. `‑‑match=`…) to be relative to mismatch score (instead of match score).
|  | Made the `<start>#<length>` file subrange action better at checking errors, and also allowed `<length>` to use units such as M and K.
|  | Sped up program exit by no longer freeing dynamically allocated memory.
1.1.0 | Dec/5/2008 | Improved x-drop extension to better handle suboptimal HSPs. Left-extension now starts at the right end of the seed (rather than the left end). This reduces the chance that the extended region (the combination of left and right extensions) will score less than some subinterval.
|  | Changed coverage filtering so that it is relative to whichever sequence is shortest. Previously it was always relative to the query.
|  | Changed defaults for xdrop and ydrop when `‑‑match` scoring is used.
|  | Interpolation now uses the xdrop value from the main alignment. Previously it used the ydrop value to match BLASTZ, but we have decided that was a bug in BLASTZ.
|  | Added `general` output format.
|  | Added `‑‑maxwordcount`.
|  | Added `‑‑notrivial`.
|  | Corrected problem with `‑‑subset` action, which wasn't using mangled sequence names.
|  | Fixed problem in writing LAV m- and x-stanzas.
|  | Blocked the use of scoring inference in the integer build, and blocked gap scoring inference in all builds.
|  | Changed much of the syntax for options and actions. The newer syntax is clearer and more consistent than the older. The older is still supported by the program so that existing scripts will still work, but it is not documented.
|  | Changed reporting of duplicated options from `can't understand "<option>"` to `duplicated or conflicting option "<option>"`.
|  | Added `‑‑format=rdotplot` option.
1.1.25 | Feb/5/2009 | Fixed a bug that caused some gapped extensions to be terminated prematurely. In some cases this also allowed a nearby low-scoring alignment to "piggyback" onto the remainder of a terminated alignment, gaining enough in score to pass the score threshold.
|  | Added support for target capsule files.
|  | Added support for `‑‑format=cigar`.
|  | Added the `<center>^<length>` sequence interval specifier.
|  | Corrected the behavior of `‑‑exact` regarding lowercase and non-ACGT characters. `‑‑exact` now considers, e.g., a lowercase A to be a match for an uppercase A. Further, any non-ACGT characters now stop the match.
|  | Improved detection and reporting of memory allocation overflow. Two problems were fixed as part of this: (1) allocation of single blocks larger than 2 Gb was being rejected even on platforms that could support larger blocks, and (2) an allocation overflow problem which could cause a segfault for target sequences longer than about 1 Gb (these require allocation of a block larger than 4 Gb).
|  | Changed the behavior when encountering an empty sequence in a file with many sequences. Previously this was reported as an error, and the program halted. Now it is reported as a warning (to `stderr`), and the program continues.
|  | Added the `‑‑output` option. In some batch systems, it is difficult to redirect `stdout` into a file, so this option allows the user to do it directly.
|  | Removed `‑‑quantum` and `‑‑code` options, replacing them with the `quantum` and `quantum=<code_file>` sequence specifier actions. This is in preparation for allowing a quantum target sequence.

1.1.50

Mar/16/2009

Fixed two problems with exact-match extension. First, when both target and query used the `multiple` sequence specifier action, exact match extension was able to skip the boundary between sequences (this problem was introduced in 1.1.25). Second, when the exact match should have extended to the end of the sequence, it was being cut short by 1 bp (on either end). The latter problem was only evident for `‑‑nogapped`; a gapped entension recovered the additional bases.

Fixed several problems with `‑‑segment=<file>`. First, if the file contained more than 4,000 segments, on some platforms the program would segfault. Second, if a sequence subrange was being used, the limit test comparing the segment interval to the subrange was incorrect. Third (if the user was lucky enough to avoid the first two problems), if a segment was on the negative strand it was improperly mapped to the subrange.

|  | Added `‑‑noytrim` to prevent y-drop mismatch shadow, improving LASTZ’s ability to align short reads.
|  | Set the default gapped extension score threshold to inherit the lowest HSP score in the case where `‑‑hspthresh=top<basecount>` or `‑‑hspthresh=top<percentage>%` is used but `‑‑gappedthresh=<score>` is not (and gapped extension is performed). Previously this case was trapped by a low level routine and the alignment was halted.
|  | Fixed a problem with the `start2+` field of `‑‑format=general`. The position was left blank for alignments on the + strand.
|  | Fixed a problem in which `‑‑writecapsule` was rejected if `‑‑seed=match<length>` was used.
|  | Fixed a problem related to name mangling which caused an "internal error" to be reported.
|  | Fixed a problem whereby single-symbol identifiers were not recognized in quantum code files.
|  | End of sequence limit checking for `<start>#<length>` and `<center>^<length>` sequence specifier actions is now "soft". If the resulting interval is beyond the end of the sequence it is truncated.
|  | Changed how `‑‑format=cigar` reports alignments on the negative strand. Apparently there is no complete spec for CIGAR format. Matching what I see output by exonerate for certain cases is the best I can do.
|  | Quantum code files can now specify probabilities as fractions. This gives a clearer representation for motif-like sequences derived from a multiple alignment.
|  | Added `cigar` field for `‑‑format=general`.
|  | Added `shingle` field for `‑‑format=general`.
|  | Added the `‑‑rdotplot=<file>` option.
|  | The `‑‑notrivial` option now works with the `multiple` sequence specifier action.
|  | Added `‑‑markend`.
|  | Added `nameparse=darkspace`.
|  | Modifed the build process to accomodate the Solaris platform.
1.1.52 | Mar/24/2009 | Fixed a bug that occurred when ydrop was less than the penalty for a one-base gap (the sum of open and extend penalties). In this case, a bug in the initialization of the DP matrix resulted in no gapped alignments ever being found.
|  | Fixed a problem with the combination of ‑‑recoverseeds and ‑‑exact. Recovered seeds were cut short by one base on the left end.
|  | Added `‑‑format=segments` option. This was later replaced by `‑‑writesegments`.

Added a workaround in the source code for what appears to be a bug in gcc 4.3.2 (see http://gcc.gnu.org/bugzilla/show_bug.cgi?id=37861). Without the workaround, the build fails with this message:

        quantum.c: In function 'generate_dna_ball':
        quantum.c:347: error: array subscript is above array bounds

The workaround uses an ifdef that specifically targets gcc 4.3.2.

1.02.00 | Jan/12/2010 | Relaxed the rejection of some output formats, which was too aggressive. Specifically, runs with `‑‑tableonly` were rejected because of output format, even though no output would be generated in that format.
|  | Added the ability to set the `‑‑maxwordcount` option as a percentage. Also, `‑‑maxwordcount=<limit>` now allows `<limit>` to be 1. Previously it was not allowed to be less than 2.

The scoring matrix used during x-drop extension now reflects the use of `‑‑ambiguous=n`. Previously, this matrix was not affected by `‑‑ambiguous=n`, and N-vs-N matches and N-vs-other matches were scored as -100 (more specifically, as `fill_score`) during gap-free extension. This caused LASTZ to miss some HSPs, usually those containing an N-vs-N match, since the HSP was terminated at that match and didn't meet the score threshold. This has been corrected.

|  | Added support for HSX indexes, to support random access into FASTA files. This improves the speed of aligning a single read (from a file of half a million) by a factor of about 12.
|  | Added `‑‑softmask=<mask_file>` file action to permit soft masking of specified intervals. Also added masking of the interval complements — `‑‑xmask=keep:<mask_file>`, `‑‑nmask=keep:<mask_file>`, and `‑‑softmask=keep:<mask_file>`. These make it easier to restrict alignment to several specified intervals of a sequence.

Enabled the use of `‑‑filter=[<transv>,]<matches>` for non-halfweight seeds. Previously, `‑‑filter` had only been tested for half-weight seeds, but was erroneously prohibited for all seeds (instead of just prohibiting non-halfweight seeds). Further, it was not properly implemented for seed-only output (`‑‑nogfextend ‑‑nogapped`). These have all been corrected, and `‑‑filter` is now available for all seed types.

Also corrected the behavior of `‑‑filter` regarding lowercase and non-ACGT characters. `‑‑filter` now considers, e.g., a lowercase `a` to be a match for an uppercase `A`. Further, for the purposes of `‑‑filter`, any non-ACGT characters are considered to be transversions.

Also changed the behavior when the `<transv>` field is absent. This is now interpreted as unlimited transversions. Previously it meant that no transversions were allowed. This should be a safe change in behavior since it was (unintentionally) not possible for users to access this feature previously.

|  | Added a compile-time directive `compileForWindows` to make appropriate behavioral adjustments for running on a Windows machine. Currently this only affects the handling of file paths. To activate it, the user must add `-DcompileForWindows` to the definition of `definedForAll` in `.../lastz‑distrib‑X.XX.XX/src/Makefile`.

Fixed chaining of seed hits. Previously, if `‑‑nogfextend` and `‑‑chain` were used together, nothing was output. This was due to the fact that unextended seeds had no scores, and the chaining algorithm only reports chains with positive score. This has been corrected by calculating scores (as the sum of substitution scores) over anchor segments whenever (a) the segments have not had scores computed for them, and (b) scores are required for later processing.

This change may also affect (for the better) the results of gapped extension when either `‑‑nogfextend` or `‑‑exact` is used. Gapped extension processes the anchors highest score first. Since `‑‑nogfextend` left all scores zero, the actual order in which gapped extension was performed in that case was dependent on how the sort routine (the C runtime routine qsort) deals with ties. For `‑‑exact`, the score was the length of the match. This has been changed to the segment’s substitution score.

|  | Changed `‑‑format=segments` to `‑‑writesegments=<file>`.
|  | Added M-mismatch extension.
|  | Added the replacement of `{number}` in sequence nicknames.
|  | Added support for continuity reporting and `filtering`.
|  | Added support for match count `filtering`.

Fixed a bug in handling subrange actions for nib files. The problem occurred when the subrange action was of the form `<start>..` and `<start>` was even. That is, no `<end>` was specified, and LASTZ is supposed to use the remainder of the sequence. LASTZ miscalculated the length of the interval, making it one base longer. If the actual full sequence length was odd, this resulted in an extra `T` being appended to the sequence data. If the full sequence length was even, LASTZ quit, reporting that it was unable to read the sequence. Note that this only happened for .nib files, only when `<start>` when even, and only when no `<end>` was specified.

|  | Added the `subsample` action.
|  | Added the `‑‑anyornone` option.
|  | Added `‑‑allgappedbounds`.
|  | Fixed a bug in exact and mistmach extension and queries using the `multiple` action. It was possible for an HSP to cover parts of two different queries.
|  | Fixed an overflow bug in the chaining algorithm. Due to numerical overflow, very high scoring HSPs were treated as negatively scoring, and thus were not included in final chains. With default scoring values, overflow was caused by the equivalent of an exact match of about 22Mbases. This problem also existed in BLASTZ.
|  | Added support for output in SAM format.
|  | Corrected dotplot output. Previously, some of the coordinate values were inconsistent and off by one.
|  | Added `‑‑progress=[<N>]`. This existed as an unadvertized option in earlier versions of the program, as `‑‑debug=queryprogress=<N>`. It has now been promoted to a first class option.
|  | Added `‑‑ambiguous=iupac` and changed `‑‑ambiguousn` to `‑‑ambiguous=n`. the former is still supported, but not advertized.
|  | Column headers for `‑‑format=general` now match the command-line keywords. Previously, all related keywords shared the same column header. For example, keywords `start2`, `zstart2`, `start2+` and `zstart2+` all produced the same column header, `start2`, in the output file. Also added `‑‑format=general-`.
|  | Now using inttypes.h macros for sized-types. This is to satisfy some additional type-checking pickiness that appears to have added to gcc version 4.2.1. In the unlikely even that a compiler doesn't support inttypes.h, the compile-time definition `override_inttypes` can be used.
|  | Added `nmatch`, `nmismatch`, `ngap`, `cgap` and `cigarx` fields for `‑‑format=general`.
|  | Added `‑‑format=mapping`, a shortcut for typical fields for `‑‑format=general` for mapping reads.
1.02.11 | Aug/21/2010 | Fixed the `cigarx` field for `‑‑format=general`, so that a run length of 1 is omitted for indels.
|  | Fixed the behavior of `‑‑recoverseeds`, which was failing to recover many HSPs when seed denisty was high. This was due to left extension being blocked by other seeds on that same hash-equivalent diagonal. Left extension is now unblocked when `‑‑recoverseeds` is enabled.
|  | Changed/corrected how the `‑‑segment` option handles wildcard names when the `multiple` action in used. To support this, the `rewind` command was added to the segments file format.
|  | Sequence masking actions (`softmask`, `xmask` and `nmask`) are now allowed for the `multiple` action.
|  | Command-line arguments beginning with two unicode non-breaking hyphens are now recognized. Since these are used in some places within this README file, it is natural for a user to copy them to the command line. Previously these were not recognized, which led to a somewhat confusing error message.

Fixed detection and reporting of improper gap penalties. Because the first base in a gap is penalized as open+extend, open can be zero or negative as long as that sum is strictly positive. Previously, a sum of zero was permitted, and a negative sum was misleadingly reported as a problem with the open penalty. Now, the sum must be strictly positive, and when it isn't the message more accurately describes the problem.

Fixed the implementation of `‑‑self` with regard to mirror-image pairs. Previously, alignments were internally restricted to be above the main diagonal in the ungapped stage only. The mirrored twins were created prior to the gapped stage, and the gapped stage operated on the full set of anchors. This had two undesirable effects -- there was little computational savings, and the resulting set of alignments could be assymetrical (due to small variations in gap positioning). This behavior has been changed so that the above-diagonal restriction occurs throughout the alignment process and mirrored twins are created just prior to output.

1.02.16 | Nov/2/2010 | Fixed a problem with `‑‑self`, introduced in 1.02.11. The problem manifested itself on 64-bit CPUs, with an error message indicating it was attempting to allocate 17 billion bytes for edit_script_copy. This has been corrected.
|  | Corrected a problem in LAV output, in which the d stanza reported an incorrect value for K or L (the ungapped and gapped soring thresholds) when they were not equal to each other. Which value was reported incorrectly depends on nuances of the compiler and could differ by platform. Alignments were not affected.
|  | Changed the error message when a fasta file contains bad characters. The previous message caused confusion when the bad character happened to be punctuation. Now the error message explicitely describes the offending character (comma, ampersand, etc.).
|  | Added `‑‑format=blastn`.
|  | Added `idfrac`, `id%`, `blastid%`, `covfrac`, `cov%`, `confrac`, `con%`, `ncolumn`, and `npair` fields for `‑‑format=general`.
|  | Added `start..end+zoom%` subrange specifier.

1.02.23

Jan/10/2011

Fixed a problem that occurred if the gap extension penalty was set to zero. This caused a divide by zero (which is reported in different ways on different platforms) and the program crashed. This has been corrected by trapping the offending division. However, the fix increases memory usage. Moreover, it is highly likely to cause truncated alignments. It’s not clear that there is any useful reason to set gap extension to zero.

|  | Added `‑‑format=rdotplot+score` and `‑‑rdotplot+score=<file>`.
|  | Improved `‑‑masking=<count>` so that it can allow a count threshold greater than 254.
|  | Fixed a problem with `‑‑scores=<scoring_file>`. When the `<scoring_file>` defined score values for `N`, those scores were not honored during the ungapped seed extension stage.

Fixed problems with `‑‑ambiguous=n` and `‑‑ambiguous=iupac`. These were incorrectly penalizing substitutions between non-ambiguous nucleotides (`A, C, G, or T`) and ambiguous ones (`N, B, D, H, K, M, R, S, V, W,` or `Y`). This has been corrected to honor the original intent, which was clearly to score these as zero.

However, for users who desire the previous behavior, a substitution penalty can now be specified with each of these options. To match the previous behavior, a penalty of twice the gap extension should be used.

A later change history item is also relevant.

|  | Added `‑‑queryhsplimit=<n>`.
1.02.27 | Jan/31/2011 | Added `‑‑outputmasking=<file>`.
1.02.37 | Mar/31/2011 | Added `‑‑outputmasking:soft=<file>`.
|  | Added example of filtering with shell commands.
|  | Changed the interpretation of comments in sequence name files. Previously, the first # was considered a comment. The implemenation predated the author’s familiarity with Illumina read names (which contain a #). In order to still allow lines that contain a read name and a comment, a # is not considered a comment unless it is is preceded by whitespace or the start of the line.

Changed the behavior of `‑‑queryhsplimit=<n>` to better match user expectations. Previously the limit was applied separately for each strand of the query. Moreover, HSPs discovered before the limit was reached were still passed downstream for further processing.

This has all been changed so that the limit applies to the combined total of HSPs for query, and if the limit is reached (exceeded), all HSPs for the read are discarded and no downstream processing is performed.

|  | Fixed a bug involving the `ngap` and `cgap` fields for `‑‑format=general`. These fields were only reported correctly if the `continuity` or `ncolumn` fields were also requested. Otherwise, the value reported represented the contents of unitialized memory.
|  | Added filtering options `‑‑filter=nmismatch:0..<max>`, `‑‑filter=ngap:0..<max>`, and `‑‑filter=cgap:0..<max>`. Also changed the option name for match count filtering to `‑‑filter=nmatch:<min>`. The older option, `‑‑matchcount=<min>` is of course still recognized.
1.02.40 | Apr/7/2011 | Added `‑‑outputmasking+=<file>` and `‑‑outputmasking+:soft=<file>`.
|  | Added `‑‑progress+masking=[<N>]`. This existed as an unadvertized option in earlier versions of the program, as `‑‑debug=queryprogress+masking=<N>`. It has now been promoted to a first class option.
|  | Added an example of how to create a soft-masked sequence by self-masking.
1.03.00 | Jul/14/2011 | When a subrange was used, the wrong denominator was used to compute coverage. The denominator used was the length of the subrange instead of the entire sequence. This adversely affected both the `‑‑filter=coverage` filter and the coverage output field. This has been corrected to use the length of the entire sequence.
|  | Added the `separator=<character>` action, allowing the user to specify a character which alignments will not cross. See also Non-ACGT Characters, Splicing, and Separation.
|  | Added support for reading FASTQ files. Quality values do not participate in alignment, but are copied to alignment output when appropriate.
|  | Added `‑‑format=general` fields `nucs1`, `nucs2` (the entire target or query nucleotides sequence), `quals1` and `quals2` (the target or query base-call quality sequence).
|  | Fixed a minor problem with the `‑‑format=general` fields `cov%` and `con%`. Those fields were being written with an extra tab character preceeding them. This had a detrimental affect on downstream parsers that required tabs as separators (parsers that interpreted whitespace as separators were not affected).
|  | Added `‑‑readgroup=<tags>`, allowing the specification of tags for SAM's `‑RG` header line.
|  | Added `‑‑allocate:target=<bytes>` and `‑‑allocate:query=<bytes>`. These allow the user to predict the amount of memory needed to store target or query sequence data, which in some instances can resolve memory overuse (it saves LASTZ from incrementally predicting the amount of memory needed). For consistency, `‑‑allocate:traceback=<bytes>` is now renamed (from `‑‑traceback=<bytes>`).
|  | Added `‑‑include=<file>`, allowing command-line arguments to be read from a text file.
|  | Updated the Yasra shortcuts. Some options that improved alignment read mapping had not previously been included in the Yasra definitions, because these options did not exist when the Yasra shortcuts were originally defined. To allow backward compatibility, the shortcuts now permit specification of a particular version of LASTZ. See the description of the shortcuts for details.
1.03.02 | Jul/19/2011 | Fixed a bug in `‑‑format=axt` and `‑‑format=axt+`, which caused every alignment to be reported twice. The bug had been introduced in version 1.02.28 (not present in 1.02.27, present in 1.02.37).
1.03.34 | Apr/12/2013 | Fixed a problem with `‑‑self` and `‑‑format=lav`, introduced in 1.02.11, which caused lastz to segfault.
|  | Fixed a bug in `‑‑writecapsule`. When the target was larger than ≈1 billion bp, an internal sanity check triggered incorrectly, stopping the program and reporting "internal error writing to" the capsule file.
|  | Fixed a bug related to `‑‑nogfextend`. If no `‑‑gappedthresh` was set, the gapped threshold incorrectly was set to 0 instead of the correct default of 3000. This has been corrected.
|  | The match count filter now allows the count to be specified as a percentage of the query length (`‑‑filter=nmatch:<min>%`).
|  | Added `‑‑format=general` fields `number1`, `number2`, `number` and `znumber` (sequence and alignment numbers).
|  | Added `‑‑format=general` fields `qalign1` and `qalign2` (quality sequences in alignment order).
|  | Corrected `rdotplot` output when the query files contains more than one sequence. Previously, the header line containing sequence names was only written once, at the beginning of the file. Now it is written once for each query sequence.

Added a warning when a scores file is used (`‑‑scores`), with the scale of the scoring matrix substantially different from the default scoring matrix, and the user hasn't set the hsp threshold or gapped threshold. This is a common mistake and often results in no alignments being found.

The warning looks something like this:

      WARNING. Scores file may warrant setting of thresholds absent from scores.txt.
      Minimum match score is 10, for matrix entry (A,A).
      This may not work well with default --gappedthresh=3000.

|  | Added `‑‑queryhspbest=<n>`.
|  | Added `‑‑querydepth=<n>`.
|  | Added alignment chores files, `‑‑chores=<file>` option, `chores=<file>` action, and `chore` field for `‑‑format=general`. See Aligning Many Subintervals.
|  | Fixed a bug related to the `nickname=<name>` action. If the corresponding sequence file was in 2Bit format, the nickname wasn't used and sequence names were copied from the sequence file. This has been corrected.
|  | Added `‑‑help=defaults` and `‑‑show=defaults`.

Fixed a problem which caused runaway memory allocation of the traceback row buffer. The problem was discovered when an alignment of a 72-bp read to a reference genome needed to allocate 170 million rows (about 700M bytes). This has been corrected.

It is not clear whether this had any affect on the alignments produced. In the examples used for testing and debugging, alignments were not affected. The negative affect was memory requirements and possibly runtime.

However, the cause of the problem was incorrect determination of bounding alignments when performing gapped alignment backwards from the anchor. So it is possible that this could have caused a desirable alignment to have been missed, truncated, or to contain suboptimal gap placement.

|  | Corrected the behavior when `‑‑anyornone` was used with `‑‑nogapped`. Previously this failed with a message indicating an internal error ("gapped_extend was given a NULL traceback pointer.").
|  | Score thresholds can now make use of units (e.g. `‑‑hspthresh=5K` instead of `‑‑hspthresh=5000`).
|  | Detection of trivial self-alignments has been improved for cases where the `multiple` action is used.
|  | The implementation of `‑‑self` has been reworked so that it no longer reads the input file twice. As a result, `‑‑self` now supports a file piped into stdin.
|  | Added an additional build (`lastz_32`) to address aligning to whole genomes larger than 2 gigabases.
|  | Changed the option names for identity, continuity and coverage filtering to `‑‑filter=identity:<min>[..<max>]`, `‑‑filter=continuity:<min>[..<max>]`, and `‑‑filter=coverage:<min>[..<max>]`. This change was made to achieve consistency with the other back-end filtering options. The older options, `‑‑identity`, `‑‑continuity` and `‑‑coverage` are of course still recognized.
1.03.46 | Oct/2/2013 | Added the `namejoin` action, to allow better handling of input files that have spaces in sequence names (e.g. Illumina casava version 1.8 fastq files).
|  | Greatly improved speed for the use case where the target contains a large number of sequences (e.g. 100 thousand exons). This was essentially a bug which had no effect on accuracy. A data structure was being repeatly allocated and erased, and was much larger than was needed (e.g. 12 Mbytes per query), and since all writes were cache misses, this ended up being very significant.
|  | Added the allowBackToBackGaps build option. Previous versions of LASTZ (and BLASTZ) did not consider alignments in which an insert was immediately adjacent to a delete (or vice versa).
|  | Fixed a problem in `‑‑format=differences` that was inadvertantly introduced in 1.03.34. A failsafe check for an unhandled case was added in that version, and `‑‑format=differences` wasn't being handled. Unfortunately this prevented this format from being usable. This has been corrected.
1.03.52 | Jan/14/2014 | Corrected a bug that occured when the `‑‑inner` option is used with the `multiple` action. With this combination lastz could report alignments straddling two sequences. This is now prevented. This bug has existed in all previous versions of lastz. It was not in blastz since blastz did not provide the ability to have multiple sequences in memory.
1.03.54 | Jan/28/2014 | Modified `‑‑ambiguous=n` and `‑‑ambiguous=iupac` to allow a reward for matches to be specified in addition to the penalty for mismatches. An earlier change history item is also relevant.

1.03.66

Jan/19/2015

Fixed an error that would cause a segfault. The causitive conditions at the user level are not well characterized. In the discovered example both target and query sequences contained 1K bp bursts of similar but highly diverged low complexity sequence, but the specific relationship (if there is one) between this feature and the failure are not known. Internally the problem resulted from an unsigned index variable attempting to become negative.

|  | Fixed an error that would cause a segfault if fasta queries were piped from stdin and the first query was empty.
|  | Added a sanity check to scoring inference. It is possible that, for a candidate scoring set, the enforcement of identity filter settings (min_identity and max_identity) leaves the inference with no alignments from which to infer scores. This condition should now result in a failure message.
|  | Changed how back-to-back gaps are represented in `lav format`, to match the way `BLASTZ` represented them. A zero-length segment is now written to the file, separating the two gaps. It has been discovered that at least one of the lav-processing tools in the Miller Lab suite expects to have such a segment.
|  | Fixed an error which prevented `‑‑progress[=<N>]` being reported for empty sequences.

1.03.73

Jul/8/2015

Eliminated alignments that begin or end with gaps. Such alignments do not make sense biologically.

Earlier versions could report a gap at either end of an alignment if the alignment was very close to an alignment found earlier in the process. This is a failure in the logic that prevents alignments from crossing (or overlapping) and/or assumptions made in extending HSPs when the anchor point is very close to a previously-found alignment. The current solution truncates the alignment by trimming away any end gaps and rescoring.

1.04.00 | Mar/12/2017 | Corrected a bug involving chaining. Previously, if `‑‑chain` and `[multiple]` were used together, the chaining algorithm incorrectly considered all sequences together as a single entity, and found a single chain across all sequences. This has been corrected, and the chaining algorithm is now performed independently for each sequence.

Implemented a workaround for parsing conflicts between sequence specifier actions and shells that use square brackets for filename expansion.

In such shells appending any action to a filename, such as `[multiple]`, caused the shell to report "lastz: no match". To provide a means for specifying actions without having to surround them in square brackets, the commands `‑‑action:target=<action>` and `‑‑action:query=<action>` have been added.

|  | Fixed an error that would cause a segfault when there are more than about 32 million HSPs. The program now detects this error case and suggests ways to avoid the situation.
1.04.03 | Nov/14/2019 | Fixed a problem with blastn format when `‑‑nogapped` was used. The q.end column was incorrect (it had the query length concatentated to it). For more details see issue 3 and issue 20 at the lastz github repository.
|  | There was an error in LAV output when an adaptive HSP threshold was used. The HSP threshold is adaptive if `‑‑hspthresh=top<basecount>` or `‑‑hspthresh=top<percentage>%` is used. In this case, forward-strand alignments were not properly tagged as forward strand. This has been corrected. For more details see issue 14 at the lastz github repository.
|  | A potential overflow error with `‑‑inner` was corrected. A 32-bit absolute value function was used on 33-bit signed inputs. No occurrences of this error have been reported; however, the error could have occurred and gone unnoticed. I have not investigated in detail, but it probably could only have occurred on alignments with coordinates more than 2Gbp apart. This has been corrected.
|  | Additional self-tests have been added. See the "testing" section in `src/Makefile` for a list.
|  | Several changes were made to the source code to placate compiler warnings. These changes have no affect on the executable.
1.04.15 | Aug/27/2021 | Fixed a bug in which the setting for `‑‑queryhspbest` was ignored. For more details see issue 28 at the lastz github repository.
|  | Added several sanity checks to prevent possible segfaults.
|  | Added PAF format.
|  | Updated the python scripts in the tools directory to be compatible with python3. The older scripts have been moved to the tools.python2 directory.
|  | Added code to properly distinguish between char and int types in parsing input files (some compilers treat chars as signed, other treat them as unsigned). For more details see issue 23 at the lastz github repository.
|  | Added Makefile.warnings.
|  | Some changes were made to the source code to placate compiler warnings. These changes have no affect on the executable.
1.04.22 | Aug/7/2022 | Fixed a serious bug in the blastn format. In previous versions query positions were misreported for alignments on opposite strands. Blastn (the program) always reports the position of the query along the forward strand. Previous versions of lastz reported it along the aligning strand. This has been corrected. For more details see issue 51 at the lastz github repository.
1.04.41 | Dec/18/2024 | `--allocate:traceback=<bytes>` is now limited to a maximum of 2G. In earlier versions, setting this to more that 2G caused a bug in the gapped alignment stage. This is now prevented by limiting the setting to 2G. For more details see issue 52 at the lastz github repository.
|  | Fixed a bug in cigar outputs. In earlier versions, the length of any run of matches longer than about 2 billion would be misreported (due to signed integer overflow at 31 bits). This has been corrected.
|  | Added `--band=<width>` to restrict self-alignment to a band above the diagonal. This may be useful in identifying diverged tandem repeats.
|  | Added `--axt=<file>` and `--maf=<file>` to allow alignments to be written in more than one format in a single run.
|  | Added entropy1 and entropy2 fields for general output.
|  | Added `--progress:hspsearch=<N>`, `--progress:filter=<N>`, and `--progress:segments=<N>` to provide better feedback on the state of the search.
|  | A change has been made to the way the score type is defined in the Makefile. The previous implementation was reported to have caused problems in some build systems.
1.04.43 | Feb/15/2025 | Added options to support the use of the operators "=" and "X" in CIGAR strings for the SAM file format. See `‑‑eqx`, `‑‑format=sam+eqx`, or `‑‑format=softsam+eqx`.
1.04.45 | Feb/24/2025 | Added the lastz_40 build, to address a narrow use case of aligning relatively small queries to a genome larger than 4 gigabases.
1.04.52 | Apr/2/2025 | Several minor source code changes that should have no effect on operation. These are mostly to prevent newer compilers complaining about source code layout, and a couple related to errors in code intended to detect numeric overflow when parsing command line options.

## References

Bellman R (1957). Dynamic Programming. Princeton University Press, Princeton, NJ.

Buhler J, Keich U, Sun Y (2003). Designing seeds for similarity search in genomic DNA. Proc. 7th Annual International Conference on Research in Computational Molecular Biology (RECOMB '03), pp. 67-75.

Chiaromonte F, Yap VB, Miller W (2002). Scoring pairwise genomic sequence alignments. Pacific Symposium on Biocomputing 7:115-126.

Cock PJA, Fields CJ, Goto N, Heuer ML, Rice PM (2009). The Sanger FASTQ file format for sequences with quality scores, and the Solexa/Illumina FASTQ variants. Nucleic Acids Research 38:1767-1771.

Gusfield D (1997). Algorithms on strings, trees and sequences. Cambridge University Press, Cambridge, pp. 244.

Harris RS (2007). Improved pairwise alignment of genomic DNA. Ph.D. thesis, Pennsylvania State University.

Li H et al. (2009). The Sequence Alignment/Map (SAM) format and SAMtools. Bioinformatics 25:2078-2079.

Myers EW, Miller W (1989). Approximate matching of regular expressions. Bull. Math. Biol. 51:5-37.

Zhang Z, Berman P, Miller W (1998). Alignments without low-scoring regions. J. Comput. Biol. 5:197-210.

## Acknowledgments

Thanks for to Haibao Tang for contributing an example implemention for BLASTN output.