# Bio.SeqIO.QualityIO module

Bio.SeqIO support for the FASTQ and QUAL file formats.

Note that you are expected to use this code via the Bio.SeqIO interface, as shown below.

The FASTQ file format is used frequently at the Wellcome Trust Sanger Institute to bundle a FASTA sequence and its PHRED quality data (integers between 0 and 90). Rather than using a single FASTQ file, often paired FASTA and QUAL files are used containing the sequence and the quality information separately.

The PHRED software reads DNA sequencing trace files, calls bases, and assigns a non-negative quality value to each called base using a logged transformation of the error probability, Q = -10 log10( Pe ), for example:

    Pe = 1.0,         Q =  0
    Pe = 0.1,         Q = 10
    Pe = 0.01,        Q = 20
    ...
    Pe = 0.00000001,  Q = 80
    Pe = 0.000000001, Q = 90

In typical raw sequence reads, the PHRED quality valuea will be from 0 to 40. In the QUAL format these quality values are held as space separated text in a FASTA like file format. In the FASTQ format, each quality values is encoded with a single ASCI character using chr(Q+33), meaning zero maps to the character “!” and for example 80 maps to “q”. For the Sanger FASTQ standard the allowed range of PHRED scores is 0 to 93 inclusive. The sequences and quality are then stored in pairs in a FASTA like format.

Unfortunately there is no official document describing the FASTQ file format, and worse, several related but different variants exist. For more details, please read this open access publication:

    The Sanger FASTQ file format for sequences with quality scores, and the
    Solexa/Illumina FASTQ variants.
    P.J.A.Cock (Biopython), C.J.Fields (BioPerl), N.Goto (BioRuby),
    M.L.Heuer (BioJava) and P.M. Rice (EMBOSS).
    Nucleic Acids Research 2010 38(6):1767-1771
    https://doi.org/10.1093/nar/gkp1137

The good news is that Roche 454 sequencers can output files in the QUAL format, and sensibly they use PHREP style scores like Sanger. Converting a pair of FASTA and QUAL files into a Sanger style FASTQ file is easy. To extract QUAL files from a Roche 454 SFF binary file, use the Roche off instrument command line tool “sffinfo” with the -q or -qual argument. You can extract a matching FASTA file using the -s or -seq argument instead.

The bad news is that Solexa/Illumina did things differently - they have their own scoring system AND their own incompatible versions of the FASTQ format. Solexa/Illumina quality scores use Q = - 10 log10 ( Pe / (1-Pe) ), which can be negative. PHRED scores and Solexa scores are NOT interchangeable (but a reasonable mapping can be achieved between them, and they are approximately equal for higher quality reads).

Confusingly early Solexa pipelines produced a FASTQ like file but using their own score mapping and an ASCII offset of 64. To make things worse, for the Solexa/Illumina pipeline 1.3 onwards, they introduced a third variant of the FASTQ file format, this time using PHRED scores (which is more consistent) but with an ASCII offset of 64.

i.e. There are at least THREE different and INCOMPATIBLE variants of the FASTQ file format: The original Sanger PHRED standard, and two from Solexa/Illumina.

The good news is that as of CASAVA version 1.8, Illumina sequencers will produce FASTQ files using the standard Sanger encoding.

You are expected to use this module via the Bio.SeqIO functions, with the following format names:

> - “qual” means simple quality files using PHRED scores (e.g. from Roche 454)

> - “fastq” means Sanger style FASTQ files using PHRED scores and an ASCII offset of 33 (e.g. from the NCBI Short Read Archive and Illumina 1.8+). These can potentially hold PHRED scores from 0 to 93.

> - “fastq-sanger” is an alias for “fastq”.

> - “fastq-solexa” means old Solexa (and also very early Illumina) style FASTQ files, using Solexa scores with an ASCII offset 64. These can hold Solexa scores from -5 to 62.

> - “fastq-illumina” means newer Illumina 1.3 to 1.7 style FASTQ files, using PHRED scores but with an ASCII offset 64, allowing PHRED scores from 0 to 62.

We could potentially add support for “qual-solexa” meaning QUAL files which contain Solexa scores, but thus far there isn’t any reason to use such files.

For example, consider the following short FASTQ file:

    @EAS54_6_R1_2_1_413_324
    CCCTTCTTGTCTTCAGCGTTTCTCC
    +
    ;;3;;;;;;;;;;;;7;;;;;;;88
    @EAS54_6_R1_2_1_540_792
    TTGGCAGGCCAAGGCCGATGGATCA
    +
    ;;;;;;;;;;;7;;;;;-;;;3;83
    @EAS54_6_R1_2_1_443_348
    GTTGCTTCTGGCGTGGGTGGGGGGG
    +
    ;;;;;;;;;;;9;7;;.7;393333

This contains three reads of length 25. From the read length these were probably originally from an early Solexa/Illumina sequencer but this file follows the Sanger FASTQ convention (PHRED style qualities with an ASCII offset of 33). This means we can parse this file using Bio.SeqIO using “fastq” as the format name:

    >>> from Bio import SeqIO
    >>> for record in SeqIO.parse("Quality/example.fastq", "fastq"):
    ...     print("%s %s" % (record.id, record.seq))
    EAS54_6_R1_2_1_413_324 CCCTTCTTGTCTTCAGCGTTTCTCC
    EAS54_6_R1_2_1_540_792 TTGGCAGGCCAAGGCCGATGGATCA
    EAS54_6_R1_2_1_443_348 GTTGCTTCTGGCGTGGGTGGGGGGG

The qualities are held as a list of integers in each record’s annotation:

    >>> print(record)
    ID: EAS54_6_R1_2_1_443_348
    Name: EAS54_6_R1_2_1_443_348
    Description: EAS54_6_R1_2_1_443_348
    Number of features: 0
    Per letter annotation for: phred_quality
    Seq('GTTGCTTCTGGCGTGGGTGGGGGGG')
    >>> print(record.letter_annotations["phred_quality"])
    [26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 24, 26, 22, 26, 26, 13, 22, 26, 18, 24, 18, 18, 18, 18]

You can use the SeqRecord format method to show this in the QUAL format:

    >>> print(record.format("qual"))
    >EAS54_6_R1_2_1_443_348
    26 26 26 26 26 26 26 26 26 26 26 24 26 22 26 26 13 22 26 18
    24 18 18 18 18

Or go back to the FASTQ format, use “fastq” (or “fastq-sanger”):

    >>> print(record.format("fastq"))
    @EAS54_6_R1_2_1_443_348
    GTTGCTTCTGGCGTGGGTGGGGGGG
    +
    ;;;;;;;;;;;9;7;;.7;393333

Or, using the Illumina 1.3+ FASTQ encoding (PHRED values with an ASCII offset of 64):

    >>> print(record.format("fastq-illumina"))
    @EAS54_6_R1_2_1_443_348
    GTTGCTTCTGGCGTGGGTGGGGGGG
    +
    ZZZZZZZZZZZXZVZZMVZRXRRRR

You can also get Biopython to convert the scores and show a Solexa style FASTQ file:

    >>> print(record.format("fastq-solexa"))
    @EAS54_6_R1_2_1_443_348
    GTTGCTTCTGGCGTGGGTGGGGGGG
    +
    ZZZZZZZZZZZXZVZZMVZRXRRRR

Notice that this is actually the same output as above using “fastq-illumina” as the format! The reason for this is all these scores are high enough that the PHRED and Solexa scores are almost equal. The differences become apparent for poor quality reads. See the functions solexa_quality_from_phred and phred_quality_from_solexa for more details.

If you wanted to trim your sequences (perhaps to remove low quality regions, or to remove a primer sequence), try slicing the SeqRecord objects. e.g.

    >>> sub_rec = record[5:15]
    >>> print(sub_rec)
    ID: EAS54_6_R1_2_1_443_348
    Name: EAS54_6_R1_2_1_443_348
    Description: EAS54_6_R1_2_1_443_348
    Number of features: 0
    Per letter annotation for: phred_quality
    Seq('TTCTGGCGTG')
    >>> print(sub_rec.letter_annotations["phred_quality"])
    [26, 26, 26, 26, 26, 26, 24, 26, 22, 26]
    >>> print(sub_rec.format("fastq"))
    @EAS54_6_R1_2_1_443_348
    TTCTGGCGTG
    +
    ;;;;;;9;7;

If you wanted to, you could read in this FASTQ file, and save it as a QUAL file:

    >>> from Bio import SeqIO
    >>> record_iterator = SeqIO.parse("Quality/example.fastq", "fastq")
    >>> with open("Quality/temp.qual", "w") as out_handle:
    ...     SeqIO.write(record_iterator, out_handle, "qual")
    3

You can of course read in a QUAL file, such as the one we just created:

    >>> from Bio import SeqIO
    >>> for record in SeqIO.parse("Quality/temp.qual", "qual"):
    ...     print("%s read of length %d" % (record.id, len(record.seq)))
    EAS54_6_R1_2_1_413_324 read of length 25
    EAS54_6_R1_2_1_540_792 read of length 25
    EAS54_6_R1_2_1_443_348 read of length 25

Notice that QUAL files don’t have a proper sequence present! But the quality information is there:

    >>> print(record)
    ID: EAS54_6_R1_2_1_443_348
    Name: EAS54_6_R1_2_1_443_348
    Description: EAS54_6_R1_2_1_443_348
    Number of features: 0
    Per letter annotation for: phred_quality
    Undefined sequence of length 25
    >>> print(record.letter_annotations["phred_quality"])
    [26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 24, 26, 22, 26, 26, 13, 22, 26, 18, 24, 18, 18, 18, 18]

Just to keep things tidy, if you are following this example yourself, you can delete this temporary file now:

    >>> import os
    >>> os.remove("Quality/temp.qual")

Sometimes you won’t have a FASTQ file, but rather just a pair of FASTA and QUAL files. Because the Bio.SeqIO system is designed for reading single files, you would have to read the two in separately and then combine the data. However, since this is such a common thing to want to do, there is a helper iterator defined in this module that does this for you - PairedFastaQualIterator.

Alternatively, if you have enough RAM to hold all the records in memory at once, then a simple dictionary approach would work:

    >>> from Bio import SeqIO
    >>> reads = SeqIO.to_dict(SeqIO.parse("Quality/example.fasta", "fasta"))
    >>> for rec in SeqIO.parse("Quality/example.qual", "qual"):
    ...     reads[rec.id].letter_annotations["phred_quality"]=rec.letter_annotations["phred_quality"]

You can then access any record by its key, and get both the sequence and the quality scores.

    >>> print(reads["EAS54_6_R1_2_1_540_792"].format("fastq"))
    @EAS54_6_R1_2_1_540_792
    TTGGCAGGCCAAGGCCGATGGATCA
    +
    ;;;;;;;;;;;7;;;;;-;;;3;83

It is important that you explicitly tell Bio.SeqIO which FASTQ variant you are using (“fastq” or “fastq-sanger” for the Sanger standard using PHRED values, “fastq-solexa” for the original Solexa/Illumina variant, or “fastq-illumina” for the more recent variant), as this cannot be detected reliably automatically.

To illustrate this problem, let’s consider an artificial example:

    >>> from Bio.Seq import Seq
    >>> from Bio.SeqRecord import SeqRecord
    >>> test = SeqRecord(Seq("NACGTACGTA"), id="Test", description="Made up!")
    >>> print(test.format("fasta"))
    >Test Made up!
    NACGTACGTA

    >>> print(test.format("fastq"))
    Traceback (most recent call last):
     ...
    ValueError: No suitable quality scores found in letter_annotations of SeqRecord (id=Test).

We created a sample SeqRecord, and can show it in FASTA format - but for QUAL or FASTQ format we need to provide some quality scores. These are held as a list of integers (one for each base) in the letter_annotations dictionary:

    >>> test.letter_annotations["phred_quality"] = [0, 1, 2, 3, 4, 5, 10, 20, 30, 40]
    >>> print(test.format("qual"))
    >Test Made up!
    0 1 2 3 4 5 10 20 30 40

    >>> print(test.format("fastq"))
    @Test Made up!
    NACGTACGTA
    +
    !"#$%&+5?I

We can check this FASTQ encoding - the first PHRED quality was zero, and this mapped to a exclamation mark, while the final score was 40 and this mapped to the letter “I”:

    >>> ord('!') - 33
    0
    >>> ord('I') - 33
    40
    >>> [ord(letter)-33 for letter in '!"#$%&+5?I']
    [0, 1, 2, 3, 4, 5, 10, 20, 30, 40]

Similarly, we could produce an Illumina 1.3 to 1.7 style FASTQ file using PHRED scores with an offset of 64:

    >>> print(test.format("fastq-illumina"))
    @Test Made up!
    NACGTACGTA
    +
    @ABCDEJT^h

And we can check this too - the first PHRED score was zero, and this mapped to “@”, while the final score was 40 and this mapped to “h”:

    >>> ord("@") - 64
    0
    >>> ord("h") - 64
    40
    >>> [ord(letter)-64 for letter in "@ABCDEJT^h"]
    [0, 1, 2, 3, 4, 5, 10, 20, 30, 40]

Notice how different the standard Sanger FASTQ and the Illumina 1.3 to 1.7 style FASTQ files look for the same data! Then we have the older Solexa/Illumina format to consider which encodes Solexa scores instead of PHRED scores.

First let’s see what Biopython says if we convert the PHRED scores into Solexa scores (rounding to one decimal place):

    >>> for q in [0, 1, 2, 3, 4, 5, 10, 20, 30, 40]:
    ...     print("PHRED %i maps to Solexa %0.1f" % (q, solexa_quality_from_phred(q)))
    PHRED 0 maps to Solexa -5.0
    PHRED 1 maps to Solexa -5.0
    PHRED 2 maps to Solexa -2.3
    PHRED 3 maps to Solexa -0.0
    PHRED 4 maps to Solexa 1.8
    PHRED 5 maps to Solexa 3.3
    PHRED 10 maps to Solexa 9.5
    PHRED 20 maps to Solexa 20.0
    PHRED 30 maps to Solexa 30.0
    PHRED 40 maps to Solexa 40.0

Now here is the record using the old Solexa style FASTQ file:

    >>> print(test.format("fastq-solexa"))
    @Test Made up!
    NACGTACGTA
    +
    ;;>@BCJT^h

Again, this is using an ASCII offset of 64, so we can check the Solexa scores:

    >>> [ord(letter)-64 for letter in ";;>@BCJT^h"]
    [-5, -5, -2, 0, 2, 3, 10, 20, 30, 40]

This explains why the last few letters of this FASTQ output matched that using the Illumina 1.3 to 1.7 format - high quality PHRED scores and Solexa scores are approximately equal.

Bio.SeqIO.QualityIO.solexa_quality_from_phred(phred_quality: float) → float

  Convert a PHRED quality (range 0 to about 90) to a Solexa quality.

  PHRED and Solexa quality scores are both log transformations of a probality of error (high score = low probability of error). This function takes a PHRED score, transforms it back to a probability of error, and then re-expresses it as a Solexa score. This assumes the error estimates are equivalent.

  How does this work exactly? Well the PHRED quality is minus ten times the base ten logarithm of the probability of error:

      phred_quality = -10*log(error,10)

  Therefore, turning this round:

      error = 10 ** (- phred_quality / 10)

  Now, Solexa qualities use a different log transformation:

      solexa_quality = -10*log(error/(1-error),10)

  After substitution and a little manipulation we get:

      solexa_quality = 10*log(10**(phred_quality/10.0) - 1, 10)

  However, real Solexa files use a minimum quality of -5. This does have a good reason - a random base call would be correct 25% of the time, and thus have a probability of error of 0.75, which gives 1.25 as the PHRED quality, or -4.77 as the Solexa quality. Thus (after rounding), a random nucleotide read would have a PHRED quality of 1, or a Solexa quality of -5.

  Taken literally, this logarithic formula would map a PHRED quality of zero to a Solexa quality of minus infinity. Of course, taken literally, a PHRED score of zero means a probability of error of one (i.e. the base call is definitely wrong), which is worse than random! In practice, a PHRED quality of zero usually means a default value, or perhaps random - and therefore mapping it to the minimum Solexa score of -5 is reasonable.

  In conclusion, we follow EMBOSS, and take this logarithmic formula but also apply a minimum value of -5.0 for the Solexa quality, and also map a PHRED quality of zero to -5.0 as well.

  Note this function will return a floating point number, it is up to you to round this to the nearest integer if appropriate. e.g.

      >>> print("%0.2f" % round(solexa_quality_from_phred(80), 2))
      80.00
      >>> print("%0.2f" % round(solexa_quality_from_phred(50), 2))
      50.00
      >>> print("%0.2f" % round(solexa_quality_from_phred(20), 2))
      19.96
      >>> print("%0.2f" % round(solexa_quality_from_phred(10), 2))
      9.54
      >>> print("%0.2f" % round(solexa_quality_from_phred(5), 2))
      3.35
      >>> print("%0.2f" % round(solexa_quality_from_phred(4), 2))
      1.80
      >>> print("%0.2f" % round(solexa_quality_from_phred(3), 2))
      -0.02
      >>> print("%0.2f" % round(solexa_quality_from_phred(2), 2))
      -2.33
      >>> print("%0.2f" % round(solexa_quality_from_phred(1), 2))
      -5.00
      >>> print("%0.2f" % round(solexa_quality_from_phred(0), 2))
      -5.00

  Notice that for high quality reads PHRED and Solexa scores are numerically equal. The differences are important for poor quality reads, where PHRED has a minimum of zero but Solexa scores can be negative.

  Finally, as a special case where None is used for a “missing value”, None is returned:

      >>> print(solexa_quality_from_phred(None))
      None

Bio.SeqIO.QualityIO.phred_quality_from_solexa(solexa_quality: float) → float

  Convert a Solexa quality (which can be negative) to a PHRED quality.

  PHRED and Solexa quality scores are both log transformations of a probality of error (high score = low probability of error). This function takes a Solexa score, transforms it back to a probability of error, and then re-expresses it as a PHRED score. This assumes the error estimates are equivalent.

  The underlying formulas are given in the documentation for the sister function solexa_quality_from_phred, in this case the operation is:

      phred_quality = 10*log(10**(solexa_quality/10.0) + 1, 10)

  This will return a floating point number, it is up to you to round this to the nearest integer if appropriate. e.g.

      >>> print("%0.2f" % round(phred_quality_from_solexa(80), 2))
      80.00
      >>> print("%0.2f" % round(phred_quality_from_solexa(20), 2))
      20.04
      >>> print("%0.2f" % round(phred_quality_from_solexa(10), 2))
      10.41
      >>> print("%0.2f" % round(phred_quality_from_solexa(0), 2))
      3.01
      >>> print("%0.2f" % round(phred_quality_from_solexa(-5), 2))
      1.19

  Note that a solexa_quality less then -5 is not expected, will trigger a warning, but will still be converted as per the logarithmic mapping (giving a number between 0 and 1.19 back).

  As a special case where None is used for a “missing value”, None is returned:

      >>> print(phred_quality_from_solexa(None))
      None

Bio.SeqIO.QualityIO.FastqGeneralIterator(source: IO[str] | PathLike | str | bytes) → Iterator[tuple[str, str, str]]

  Iterate over Fastq records as string tuples (not as SeqRecord objects).

  Arguments:

    - source - input stream opened in text mode, or a path to a file

  This code does not try to interpret the quality string numerically. It just returns tuples of the title, sequence and quality as strings. For the sequence and quality, any whitespace (such as new lines) is removed.

  Our SeqRecord based FASTQ iterators call this function internally, and then turn the strings into a SeqRecord objects, mapping the quality string into a list of numerical scores. If you want to do a custom quality mapping, then you might consider calling this function directly.

  For parsing FASTQ files, the title string from the “@” line at the start of each record can optionally be omitted on the “+” lines. If it is repeated, it must be identical.

  The sequence string and the quality string can optionally be split over multiple lines, although several sources discourage this. In comparison, for the FASTA file format line breaks between 60 and 80 characters are the norm.

  WARNING - Because the “@” character can appear in the quality string, this can cause problems as this is also the marker for the start of a new sequence. In fact, the “+” sign can also appear as well. Some sources recommended having no line breaks in the quality to avoid this, but even that is not enough, consider this example:

      @071113_EAS56_0053:1:1:998:236
      TTTCTTGCCCCCATAGACTGAGACCTTCCCTAAATA
      +071113_EAS56_0053:1:1:998:236
      IIIIIIIIIIIIIIIIIIIIIIIIIIIIICII+III
      @071113_EAS56_0053:1:1:182:712
      ACCCAGCTAATTTTTGTATTTTTGTTAGAGACAGTG
      +
      @IIIIIIIIIIIIIIICDIIIII<%<6&-*).(*%+
      @071113_EAS56_0053:1:1:153:10
      TGTTCTGAAGGAAGGTGTGCGTGCGTGTGTGTGTGT
      +
      IIIIIIIIIIIICIIGIIIII>IAIIIE65I=II:6
      @071113_EAS56_0053:1:3:990:501
      TGGGAGGTTTTATGTGGA
      AAGCAGCAATGTACAAGA
      +
      IIIIIII.IIIIII1@44
      @-7.%<&+/$/%4(++(%

  This is four PHRED encoded FASTQ entries originally from an NCBI source (given the read length of 36, these are probably Solexa Illumina reads where the quality has been mapped onto the PHRED values).

  This example has been edited to illustrate some of the nasty things allowed in the FASTQ format. Firstly, on the “+” lines most but not all of the (redundant) identifiers are omitted. In real files it is likely that all or none of these extra identifiers will be present.

  Secondly, while the first three sequences have been shown without line breaks, the last has been split over multiple lines. In real files any line breaks are likely to be consistent.

  Thirdly, some of the quality string lines start with an “@” character. For the second record this is unavoidable. However for the fourth sequence this only happens because its quality string is split over two lines. A naive parser could wrongly treat any line starting with an “@” as the beginning of a new sequence! This code copes with this possible ambiguity by keeping track of the length of the sequence which gives the expected length of the quality string.

  Using this tricky example file as input, this short bit of code demonstrates what this parsing function would return:

      >>> with open("Quality/tricky.fastq") as handle:
      ...     for (title, sequence, quality) in FastqGeneralIterator(handle):
      ...         print(title)
      ...         print("%s %s" % (sequence, quality))
      ...
      071113_EAS56_0053:1:1:998:236
      TTTCTTGCCCCCATAGACTGAGACCTTCCCTAAATA IIIIIIIIIIIIIIIIIIIIIIIIIIIIICII+III
      071113_EAS56_0053:1:1:182:712
      ACCCAGCTAATTTTTGTATTTTTGTTAGAGACAGTG @IIIIIIIIIIIIIIICDIIIII<%<6&-*).(*%+
      071113_EAS56_0053:1:1:153:10
      TGTTCTGAAGGAAGGTGTGCGTGCGTGTGTGTGTGT IIIIIIIIIIIICIIGIIIII>IAIIIE65I=II:6
      071113_EAS56_0053:1:3:990:501
      TGGGAGGTTTTATGTGGAAAGCAGCAATGTACAAGA IIIIIII.IIIIII1@44@-7.%<&+/$/%4(++(%

  Finally we note that some sources state that the quality string should start with “!” (which using the PHRED mapping means the first letter always has a quality score of zero). This rather restrictive rule is not widely observed, so is therefore ignored here. One plus point about this “!” rule is that (provided there are no line breaks in the quality sequence) it would prevent the above problem with the “@” character.

class Bio.SeqIO.QualityIO.FastqIteratorAbstractBaseClass(source)

  Bases: `SequenceIterator`[`str`]

  Abstract base class for FASTQ file parsers.

  modes = 't'
  abstract property q_mapping

    Dictionary that maps letters in the quality string to quality values.

  abstract property q_key

    Key name (string) of the quality values in record.letter_annotations.

  __init__(source)

    Iterate over FASTQ records as SeqRecord objects.

    Arguments:

      - source - input stream opened in text mode, or a path to a file

    The quality values are stored in the letter_annotations dictionary attribute under the key q_key.

  __next__() → SeqRecord

    Parse the file and generate SeqRecord objects.

  __abstractmethods__ = frozenset({'q_key', 'q_mapping'})
  __annotations__ = {}
  __firstlineno__ = 1001
  __orig_bases__ = (Bio.SeqIO.Interfaces.SequenceIterator[str],)
  __parameters__ = ()
  __static_attributes__ = ('line',)

class Bio.SeqIO.QualityIO.FastqPhredIterator(source: IO[str] | PathLike | str | bytes, alphabet: None = None)

  Bases: `FastqIteratorAbstractBaseClass`

  Parser for FASTQ files.

  q_mapping = b'\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\x00\x01\x02\x03\x04\x05\x06\x07\x08\t\n\x0b\x0c\r\x0e\x0f\x10\x11\x12\x13\x14\x15\x16\x17\x18\x19\x1a\x1b\x1c\x1d\x1e\x1f !"#$%&\'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\\]\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8'
  q_key = 'phred_quality'
  __init__(source: IO[str] | PathLike | str | bytes, alphabet: None = None)

    Iterate over FASTQ records as SeqRecord objects.

    Arguments:

      - source - input stream opened in text mode, or a path to a file

      - alphabet - optional alphabet, no longer used. Leave as None.

    For each sequence in a (Sanger style) FASTQ file there is a matching string encoding the PHRED qualities (integers between 0 and about 90) using ASCII values with an offset of 33.

    For example, consider a file containing three short reads:

        @EAS54_6_R1_2_1_413_324
        CCCTTCTTGTCTTCAGCGTTTCTCC
        +
        ;;3;;;;;;;;;;;;7;;;;;;;88
        @EAS54_6_R1_2_1_540_792
        TTGGCAGGCCAAGGCCGATGGATCA
        +
        ;;;;;;;;;;;7;;;;;-;;;3;83
        @EAS54_6_R1_2_1_443_348
        GTTGCTTCTGGCGTGGGTGGGGGGG
        +
        ;;;;;;;;;;;9;7;;.7;393333

    For each sequence (e.g. “CCCTTCTTGTCTTCAGCGTTTCTCC”) there is a matching string encoding the PHRED qualities using a ASCII values with an offset of 33 (e.g. “;;3;;;;;;;;;;;;7;;;;;;;88”).

    Using this module directly you might run:

        >>> with open("Quality/example.fastq") as handle:
        ...     for record in FastqPhredIterator(handle):
        ...         print("%s %s" % (record.id, record.seq))
        EAS54_6_R1_2_1_413_324 CCCTTCTTGTCTTCAGCGTTTCTCC
        EAS54_6_R1_2_1_540_792 TTGGCAGGCCAAGGCCGATGGATCA
        EAS54_6_R1_2_1_443_348 GTTGCTTCTGGCGTGGGTGGGGGGG

    Typically however, you would call this via Bio.SeqIO instead with “fastq” (or “fastq-sanger”) as the format:

        >>> from Bio import SeqIO
        >>> with open("Quality/example.fastq") as handle:
        ...     for record in SeqIO.parse(handle, "fastq"):
        ...         print("%s %s" % (record.id, record.seq))
        EAS54_6_R1_2_1_413_324 CCCTTCTTGTCTTCAGCGTTTCTCC
        EAS54_6_R1_2_1_540_792 TTGGCAGGCCAAGGCCGATGGATCA
        EAS54_6_R1_2_1_443_348 GTTGCTTCTGGCGTGGGTGGGGGGG

    If you want to look at the qualities, they are record in each record’s per-letter-annotation dictionary as a simple list of integers:

        >>> print(record.letter_annotations["phred_quality"])
        [26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 24, 26, 22, 26, 26, 13, 22, 26, 18, 24, 18, 18, 18, 18]

    To modify the records returned by the parser, you can use a generator function. For example, to store the mean PHRED quality in the record description, use

        >>> from statistics import mean
        >>> def modify_records(records):
        ...     for record in records:
        ...         record.description = mean(record.letter_annotations['phred_quality'])
        ...         yield record
        ...
        >>> with open('Quality/example.fastq') as handle:
        ...     for record in modify_records(FastqPhredIterator(handle)):
        ...         print(record.id, record.description)
        ...
        EAS54_6_R1_2_1_413_324 25.28
        EAS54_6_R1_2_1_540_792 24.52
        EAS54_6_R1_2_1_443_348 23.4

  __abstractmethods__ = frozenset({})
  __annotations__ = {}
  __firstlineno__ = 1132
  __parameters__ = ()
  __static_attributes__ = ()

class Bio.SeqIO.QualityIO.FastqSolexaIterator(source: IO[str] | PathLike | str | bytes, alphabet: None = None)

  Bases: `FastqIteratorAbstractBaseClass`

  Parser for old Solexa/Illumina FASTQ like files.

  These files differ in the quality mapping.

  q_mapping = b'\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xfb\xfc\xfd\xfe\xff\x00\x01\x02\x03\x04\x05\x06\x07\x08\t\n\x0b\x0c\r\x0e\x0f\x10\x11\x12\x13\x14\x15\x16\x17\x18\x19\x1a\x1b\x1c\x1d\x1e\x1f !"#$%&\'()*+,-./0123456789:;<=>\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8'
  q_key = 'solexa_quality'
  __init__(source: IO[str] | PathLike | str | bytes, alphabet: None = None)

    Iterate over FASTQ records as SeqRecord objects.

    Arguments:

      - source - input stream opened in text mode, or a path to a file

      - alphabet - optional alphabet, no longer used. Leave as None.

    For each sequence in Solexa/Illumina FASTQ files there is a matching string encoding the Solexa integer qualities using ASCII values with an offset of 64. Solexa scores are scaled differently to PHRED scores, and Biopython will NOT perform any automatic conversion when loading.

    NOTE - This file format is used by the OLD versions of the Solexa/ Illumina pipeline. See also the FastqIlluminaIterator function for the NEW version.

    For example, consider a file containing these five records:

        @SLXA-B3_649_FC8437_R1_1_1_610_79
        GATGTGCAATACCTTTGTAGAGGAA
        +SLXA-B3_649_FC8437_R1_1_1_610_79
        YYYYYYYYYYYYYYYYYYWYWYYSU
        @SLXA-B3_649_FC8437_R1_1_1_397_389
        GGTTTGAGAAAGAGAAATGAGATAA
        +SLXA-B3_649_FC8437_R1_1_1_397_389
        YYYYYYYYYWYYYYWWYYYWYWYWW
        @SLXA-B3_649_FC8437_R1_1_1_850_123
        GAGGGTGTTGATCATGATGATGGCG
        +SLXA-B3_649_FC8437_R1_1_1_850_123
        YYYYYYYYYYYYYWYYWYYSYYYSY
        @SLXA-B3_649_FC8437_R1_1_1_362_549
        GGAAACAAAGTTTTTCTCAACATAG
        +SLXA-B3_649_FC8437_R1_1_1_362_549
        YYYYYYYYYYYYYYYYYYWWWWYWY
        @SLXA-B3_649_FC8437_R1_1_1_183_714
        GTATTATTTAATGGCATACACTCAA
        +SLXA-B3_649_FC8437_R1_1_1_183_714
        YYYYYYYYYYWYYYYWYWWUWWWQQ

    Using this module directly you might run:

        >>> with open("Quality/solexa_example.fastq") as handle:
        ...     for record in FastqSolexaIterator(handle):
        ...         print("%s %s" % (record.id, record.seq))
        SLXA-B3_649_FC8437_R1_1_1_610_79 GATGTGCAATACCTTTGTAGAGGAA
        SLXA-B3_649_FC8437_R1_1_1_397_389 GGTTTGAGAAAGAGAAATGAGATAA
        SLXA-B3_649_FC8437_R1_1_1_850_123 GAGGGTGTTGATCATGATGATGGCG
        SLXA-B3_649_FC8437_R1_1_1_362_549 GGAAACAAAGTTTTTCTCAACATAG
        SLXA-B3_649_FC8437_R1_1_1_183_714 GTATTATTTAATGGCATACACTCAA

    Typically however, you would call this via Bio.SeqIO instead with “fastq-solexa” as the format:

        >>> from Bio import SeqIO
        >>> with open("Quality/solexa_example.fastq") as handle:
        ...     for record in SeqIO.parse(handle, "fastq-solexa"):
        ...         print("%s %s" % (record.id, record.seq))
        SLXA-B3_649_FC8437_R1_1_1_610_79 GATGTGCAATACCTTTGTAGAGGAA
        SLXA-B3_649_FC8437_R1_1_1_397_389 GGTTTGAGAAAGAGAAATGAGATAA
        SLXA-B3_649_FC8437_R1_1_1_850_123 GAGGGTGTTGATCATGATGATGGCG
        SLXA-B3_649_FC8437_R1_1_1_362_549 GGAAACAAAGTTTTTCTCAACATAG
        SLXA-B3_649_FC8437_R1_1_1_183_714 GTATTATTTAATGGCATACACTCAA

    The qualities are recorded in each record’s per-letter-annotation dictionary as a simple list of integers:

        >>> print(record.letter_annotations["solexa_quality"])
        [25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 23, 25, 25, 25, 25, 23, 25, 23, 23, 21, 23, 23, 23, 17, 17]

    These scores aren’t very good, but they are high enough that they map almost exactly onto PHRED scores:

        >>> print("%0.2f" % phred_quality_from_solexa(25))
        25.01

    Let’s look at faked example read which is even worse, where there are more noticeable differences between the Solexa and PHRED scores:

        @slxa_0001_1_0001_01
        ACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTNNNNNN
        +slxa_0001_1_0001_01
        hgfedcba`_^]\[ZYXWVUTSRQPONMLKJIHGFEDCBA@?>=<;

    Again, you would typically use Bio.SeqIO to read this file in (rather than calling the Bio.SeqIO.QualtityIO module directly). Most FASTQ files will contain thousands of reads, so you would normally use Bio.SeqIO.parse() as shown above. This example has only as one entry, so instead we can use the Bio.SeqIO.read() function:

        >>> from Bio import SeqIO
        >>> with open("Quality/solexa_faked.fastq") as handle:
        ...     record = SeqIO.read(handle, "fastq-solexa")
        >>> print("%s %s" % (record.id, record.seq))
        slxa_0001_1_0001_01 ACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTNNNNNN
        >>> print(record.letter_annotations["solexa_quality"])
        [40, 39, 38, 37, 36, 35, 34, 33, 32, 31, 30, 29, 28, 27, 26, 25, 24, 23, 22, 21, 20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0, -1, -2, -3, -4, -5]

    These quality scores are so low that when converted from the Solexa scheme into PHRED scores they look quite different:

        >>> print("%0.2f" % phred_quality_from_solexa(-1))
        2.54
        >>> print("%0.2f" % phred_quality_from_solexa(-5))
        1.19

    Note you can use the Bio.SeqIO.write() function or the SeqRecord’s format method to output the record(s):

        >>> print(record.format("fastq-solexa"))
        @slxa_0001_1_0001_01
        ACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTNNNNNN
        +
        hgfedcba`_^]\[ZYXWVUTSRQPONMLKJIHGFEDCBA@?>=<;

    Note this output is slightly different from the input file as Biopython has left out the optional repetition of the sequence identifier on the “+” line. If you want the to use PHRED scores, use “fastq” or “qual” as the output format instead, and Biopython will do the conversion for you:

        >>> print(record.format("fastq"))
        @slxa_0001_1_0001_01
        ACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTNNNNNN
        +
        IHGFEDCBA@?>=<;:9876543210/.-,++*)('&&%%$$##""

        >>> print(record.format("qual"))
        >slxa_0001_1_0001_01
        40 39 38 37 36 35 34 33 32 31 30 29 28 27 26 25 24 23 22 21
        20 19 18 17 16 15 14 13 12 11 10 10 9 8 7 6 5 5 4 4 3 3 2 2
        1 1

    As shown above, the poor quality Solexa reads have been mapped to the equivalent PHRED score (e.g. -5 to 1 as shown earlier).

  __abstractmethods__ = frozenset({})
  __annotations__ = {}
  __firstlineno__ = 1236
  __parameters__ = ()
  __static_attributes__ = ()

class Bio.SeqIO.QualityIO.FastqIlluminaIterator(source: IO[str] | PathLike | str | bytes, alphabet: None = None)

  Bases: `FastqIteratorAbstractBaseClass`

  Parser for Illumina 1.3 to 1.7 FASTQ like files.

  These files differ in the quality mapping.

  q_mapping = b'\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\x00\x01\x02\x03\x04\x05\x06\x07\x08\t\n\x0b\x0c\r\x0e\x0f\x10\x11\x12\x13\x14\x15\x16\x17\x18\x19\x1a\x1b\x1c\x1d\x1e\x1f !"#$%&\'()*+,-./0123456789:;<=>\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8\xc8'
  q_key = 'phred_quality'
  __init__(source: IO[str] | PathLike | str | bytes, alphabet: None = None)

    Iterate over FASTQ records as SeqRecord objects.

    Arguments:

      - source - input stream opened in text mode, or a path to a file

      - alphabet - optional alphabet, no longer used. Leave as None.

    For each sequence in Illumina 1.3+ FASTQ files there is a matching string encoding PHRED integer qualities using ASCII values with an offset of 64.

        >>> from Bio import SeqIO
        >>> record = SeqIO.read("Quality/illumina_faked.fastq", "fastq-illumina")
        >>> print("%s %s" % (record.id, record.seq))
        Test ACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTN
        >>> max(record.letter_annotations["phred_quality"])
        40
        >>> min(record.letter_annotations["phred_quality"])
        0

    NOTE - Older versions of the Solexa/Illumina pipeline encoded Solexa scores with an ASCII offset of 64. They are approximately equal but only for high quality reads. If you have an old Solexa/Illumina file with negative Solexa scores, and try and read this as an Illumina 1.3+ file it will fail:

        >>> record2 = SeqIO.read("Quality/solexa_faked.fastq", "fastq-illumina")
        Traceback (most recent call last):
           ...
        Bio.SeqIO.QualityIO.InvalidCharError: Invalid character (?) or (0x3f) in quality string not in correct range (are you sure you're using the right QualityIO parser?) with context: [...BA@?>=<...]

    NOTE - True Sanger style FASTQ files use PHRED scores with an offset of 33.

  __abstractmethods__ = frozenset({})
  __annotations__ = {}
  __firstlineno__ = 1401
  __parameters__ = ()
  __static_attributes__ = ()

class Bio.SeqIO.QualityIO.QualPhredIterator(source: IO[str] | PathLike | str | bytes, alphabet: None = None)

  Bases: `SequenceIterator`

  Parser for QUAL files with PHRED quality scores but no sequence.

  modes = 't'
  __init__(source: IO[str] | PathLike | str | bytes, alphabet: None = None) → None

    For QUAL files which include PHRED quality scores, but no sequence.

    For example, consider this short QUAL file:

        >EAS54_6_R1_2_1_413_324
        26 26 18 26 26 26 26 26 26 26 26 26 26 26 26 22 26 26 26 26
        26 26 26 23 23
        >EAS54_6_R1_2_1_540_792
        26 26 26 26 26 26 26 26 26 26 26 22 26 26 26 26 26 12 26 26
        26 18 26 23 18
        >EAS54_6_R1_2_1_443_348
        26 26 26 26 26 26 26 26 26 26 26 24 26 22 26 26 13 22 26 18
        24 18 18 18 18

    Using this module directly you might run:

        >>> with open("Quality/example.qual") as handle:
        ...     for record in QualPhredIterator(handle):
        ...         print("%s read of length %d" % (record.id, len(record.seq)))
        EAS54_6_R1_2_1_413_324 read of length 25
        EAS54_6_R1_2_1_540_792 read of length 25
        EAS54_6_R1_2_1_443_348 read of length 25

    Typically however, you would call this via Bio.SeqIO instead with “qual” as the format:

        >>> from Bio import SeqIO
        >>> with open("Quality/example.qual") as handle:
        ...     for record in SeqIO.parse(handle, "qual"):
        ...         print("%s read of length %d" % (record.id, len(record.seq)))
        EAS54_6_R1_2_1_413_324 read of length 25
        EAS54_6_R1_2_1_540_792 read of length 25
        EAS54_6_R1_2_1_443_348 read of length 25

    Only the sequence length is known, as the QUAL file does not contain the sequence string itself.

    The quality scores themselves are available as a list of integers in each record’s per-letter-annotation:

        >>> print(record.letter_annotations["phred_quality"])
        [26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 24, 26, 22, 26, 26, 13, 22, 26, 18, 24, 18, 18, 18, 18]

    You can still slice one of these SeqRecord objects:

        >>> sub_record = record[5:10]
        >>> print("%s %s" % (sub_record.id, sub_record.letter_annotations["phred_quality"]))
        EAS54_6_R1_2_1_443_348 [26, 26, 26, 26, 26]

    As of Biopython 1.59, this parser will accept files with negatives quality scores but will replace them with the lowest possible PHRED score of zero. This will trigger a warning, previously it raised a ValueError exception.

  __next__() → SeqRecord

    Parse the file and generate SeqRecord objects.

  __abstractmethods__ = frozenset({})
  __annotations__ = {}
  __firstlineno__ = 1461
  __parameters__ = ()
  __static_attributes__ = ('_line',)

class Bio.SeqIO.QualityIO.FastqPhredWriter(target: IO | PathLike | str | bytes)

  Bases: `SequenceWriter`

  Class to write standard FASTQ format files (using PHRED quality scores) (OBSOLETE).

  Although you can use this class directly, you are strongly encouraged to use the `as_fastq` function, or top level `Bio.SeqIO.write()` function instead via the format name “fastq” or the alias “fastq-sanger”.

  For example, this code reads in a standard Sanger style FASTQ file (using PHRED scores) and re-saves it as another Sanger style FASTQ file:

      >>> from Bio import SeqIO
      >>> record_iterator = SeqIO.parse("Quality/example.fastq", "fastq")
      >>> with open("Quality/temp.fastq", "w") as out_handle:
      ...     SeqIO.write(record_iterator, out_handle, "fastq")
      3

  You might want to do this if the original file included extra line breaks, which while valid may not be supported by all tools. The output file from Biopython will have each sequence on a single line, and each quality string on a single line (which is considered desirable for maximum compatibility).

  In this next example, an old style Solexa/Illumina FASTQ file (using Solexa quality scores) is converted into a standard Sanger style FASTQ file using PHRED qualities:

      >>> from Bio import SeqIO
      >>> record_iterator = SeqIO.parse("Quality/solexa_example.fastq", "fastq-solexa")
      >>> with open("Quality/temp.fastq", "w") as out_handle:
      ...     SeqIO.write(record_iterator, out_handle, "fastq")
      5

  This code is also called if you use the .format(“fastq”) method of a SeqRecord, or .format(“fastq-sanger”) if you prefer that alias.

  Note that Sanger FASTQ files have an upper limit of PHRED quality 93, which is encoded as ASCII 126, the tilde. If your quality scores are truncated to fit, a warning is issued.

  P.S. To avoid cluttering up your working directory, you can delete this temporary file now:

      >>> import os
      >>> os.remove("Quality/temp.fastq")

  modes = 't'
  write_record(record: SeqRecord) → None

    Write a single FASTQ record to the file.

  __abstractmethods__ = frozenset({})
  __annotations__ = {}
  __firstlineno__ = 1580
  __parameters__ = ()
  __static_attributes__ = ()

Bio.SeqIO.QualityIO.as_fastq(record: SeqRecord) → str

  Turn a SeqRecord into a Sanger FASTQ formatted string.

  This is used internally by the SeqRecord’s .format(“fastq”) method and by the SeqIO.write(…, …, “fastq”) function, and under the format alias “fastq-sanger” as well.

class Bio.SeqIO.QualityIO.QualPhredWriter(handle: IO[str] | PathLike | str | bytes, wrap: int = 60, record2title: Callable[[SeqRecord], str] | None = None)

  Bases: `SequenceWriter`

  Class to write QUAL format files (using PHRED quality scores) (OBSOLETE).

  Although you can use this class directly, you are strongly encouraged to use the `as_qual` function, or top level `Bio.SeqIO.write()` function instead.

  For example, this code reads in a FASTQ file and saves the quality scores into a QUAL file:

      >>> from Bio import SeqIO
      >>> record_iterator = SeqIO.parse("Quality/example.fastq", "fastq")
      >>> with open("Quality/temp.qual", "w") as out_handle:
      ...     SeqIO.write(record_iterator, out_handle, "qual")
      3

  This code is also called if you use the .format(“qual”) method of a SeqRecord.

  P.S. Don’t forget to clean up the temp file if you don’t need it anymore:

      >>> import os
      >>> os.remove("Quality/temp.qual")

  modes = 't'
  __init__(handle: IO[str] | PathLike | str | bytes, wrap: int = 60, record2title: Callable[[SeqRecord], str] | None = None) → None

    Create a QUAL writer.

    Arguments:

      - handle - Handle to an output file, e.g. as returned by open(filename, “w”)

      - wrap - Optional line length used to wrap sequence lines. Defaults to wrapping the sequence at 60 characters. Use zero (or None) for no wrapping, giving a single long line for the sequence.

      - record2title - Optional function to return the text to be used for the title line of each record. By default a combination of the record.id and record.description is used. If the record.description starts with the record.id, then just the record.description is used.

    The record2title argument is present for consistency with the Bio.SeqIO.FastaIO writer class.

  write_record(record: SeqRecord) → None

    Write a single QUAL record to the file.

  __abstractmethods__ = frozenset({})
  __annotations__ = {'wrap': 'Optional[int]'}
  __firstlineno__ = 1681
  __parameters__ = ()
  __static_attributes__ = ('record2title', 'wrap')

Bio.SeqIO.QualityIO.as_qual(record: SeqRecord) → str

  Turn a SeqRecord into a QUAL formatted string.

  This is used internally by the SeqRecord’s .format(“qual”) method and by the SeqIO.write(…, …, “qual”) function.

class Bio.SeqIO.QualityIO.FastqSolexaWriter(target: IO | PathLike | str | bytes)

  Bases: `SequenceWriter`

  Write old style Solexa/Illumina FASTQ format files (with Solexa qualities) (OBSOLETE).

  This outputs FASTQ files like those from the early Solexa/Illumina pipeline, using Solexa scores and an ASCII offset of 64. These are NOT compatible with the standard Sanger style PHRED FASTQ files.

  If your records contain a “solexa_quality” entry under letter_annotations, this is used, otherwise any “phred_quality” entry will be used after conversion using the solexa_quality_from_phred function. If neither style of quality scores are present, an exception is raised.

  Although you can use this class directly, you are strongly encouraged to use the `as_fastq_solexa` function, or top-level `Bio.SeqIO.write()` function instead. For example, this code reads in a FASTQ file and re-saves it as another FASTQ file:

      >>> from Bio import SeqIO
      >>> record_iterator = SeqIO.parse("Quality/solexa_example.fastq", "fastq-solexa")
      >>> with open("Quality/temp.fastq", "w") as out_handle:
      ...     SeqIO.write(record_iterator, out_handle, "fastq-solexa")
      5

  You might want to do this if the original file included extra line breaks, which (while valid) may not be supported by all tools. The output file from Biopython will have each sequence on a single line, and each quality string on a single line (which is considered desirable for maximum compatibility).

  This code is also called if you use the .format(“fastq-solexa”) method of a SeqRecord. For example,

      >>> record = SeqIO.read("Quality/sanger_faked.fastq", "fastq-sanger")
      >>> print(record.format("fastq-solexa"))
      @Test PHRED qualities from 40 to 0 inclusive
      ACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTN
      +
      hgfedcba`_^]\[ZYXWVUTSRQPONMLKJHGFECB@>;;

  Note that Solexa FASTQ files have an upper limit of Solexa quality 62, which is encoded as ASCII 126, the tilde. If your quality scores must be truncated to fit, a warning is issued.

  P.S. Don’t forget to delete the temp file if you don’t need it anymore:

      >>> import os
      >>> os.remove("Quality/temp.fastq")

  modes = 't'
  write_record(record: SeqRecord) → None

    Write a single FASTQ record to the file.

  __abstractmethods__ = frozenset({})
  __annotations__ = {}
  __firstlineno__ = 1833
  __parameters__ = ()
  __static_attributes__ = ()

Bio.SeqIO.QualityIO.as_fastq_solexa(record: SeqRecord) → str

  Turn a SeqRecord into a Solexa FASTQ formatted string.

  This is used internally by the SeqRecord’s .format(“fastq-solexa”) method and by the SeqIO.write(…, …, “fastq-solexa”) function.

class Bio.SeqIO.QualityIO.FastqIlluminaWriter(target: IO | PathLike | str | bytes)

  Bases: `SequenceWriter`

  Write Illumina 1.3+ FASTQ format files (with PHRED quality scores) (OBSOLETE).

  This outputs FASTQ files like those from the Solexa/Illumina 1.3+ pipeline, using PHRED scores and an ASCII offset of 64. Note these files are NOT compatible with the standard Sanger style PHRED FASTQ files which use an ASCII offset of 32.

  Although you can use this class directly, you are strongly encouraged to use the `as_fastq_illumina` or top-level `Bio.SeqIO.write()` function with format name “fastq-illumina” instead. This code is also called if you use the .format(“fastq-illumina”) method of a SeqRecord. For example,

      >>> from Bio import SeqIO
      >>> record = SeqIO.read("Quality/sanger_faked.fastq", "fastq-sanger")
      >>> print(record.format("fastq-illumina"))
      @Test PHRED qualities from 40 to 0 inclusive
      ACGTACGTACGTACGTACGTACGTACGTACGTACGTACGTN
      +
      hgfedcba`_^]\[ZYXWVUTSRQPONMLKJIHGFEDCBA@

  Note that Illumina FASTQ files have an upper limit of PHRED quality 62, which is encoded as ASCII 126, the tilde. If your quality scores are truncated to fit, a warning is issued.

  modes = 't'
  write_record(record: SeqRecord) → None

    Write a single FASTQ record to the file.

  __abstractmethods__ = frozenset({})
  __annotations__ = {}
  __firstlineno__ = 1938
  __parameters__ = ()
  __static_attributes__ = ()

Bio.SeqIO.QualityIO.as_fastq_illumina(record: SeqRecord) → str

  Turn a SeqRecord into an Illumina FASTQ formatted string.

  This is used internally by the SeqRecord’s .format(“fastq-illumina”) method and by the SeqIO.write(…, …, “fastq-illumina”) function.

Bio.SeqIO.QualityIO.PairedFastaQualIterator(fasta_source: IO[str] | PathLike | str | bytes, qual_source: IO[str] | PathLike | str | bytes, alphabet: None = None) → Iterator[SeqRecord]

  Iterate over matched FASTA and QUAL files as SeqRecord objects.

  For example, consider this short QUAL file with PHRED quality scores:

      >EAS54_6_R1_2_1_413_324
      26 26 18 26 26 26 26 26 26 26 26 26 26 26 26 22 26 26 26 26
      26 26 26 23 23
      >EAS54_6_R1_2_1_540_792
      26 26 26 26 26 26 26 26 26 26 26 22 26 26 26 26 26 12 26 26
      26 18 26 23 18
      >EAS54_6_R1_2_1_443_348
      26 26 26 26 26 26 26 26 26 26 26 24 26 22 26 26 13 22 26 18
      24 18 18 18 18

  And a matching FASTA file:

      >EAS54_6_R1_2_1_413_324
      CCCTTCTTGTCTTCAGCGTTTCTCC
      >EAS54_6_R1_2_1_540_792
      TTGGCAGGCCAAGGCCGATGGATCA
      >EAS54_6_R1_2_1_443_348
      GTTGCTTCTGGCGTGGGTGGGGGGG

  You can parse these separately using Bio.SeqIO with the “qual” and “fasta” formats, but then you’ll get a group of SeqRecord objects with no sequence, and a matching group with the sequence but not the qualities. Because it only deals with one input file handle, Bio.SeqIO can’t be used to read the two files together - but this function can! For example,

      >>> with open("Quality/example.fasta") as f:
      ...     with open("Quality/example.qual") as q:
      ...         for record in PairedFastaQualIterator(f, q):
      ...             print("%s %s" % (record.id, record.seq))
      ...
      EAS54_6_R1_2_1_413_324 CCCTTCTTGTCTTCAGCGTTTCTCC
      EAS54_6_R1_2_1_540_792 TTGGCAGGCCAAGGCCGATGGATCA
      EAS54_6_R1_2_1_443_348 GTTGCTTCTGGCGTGGGTGGGGGGG

  As with the FASTQ or QUAL parsers, if you want to look at the qualities, they are in each record’s per-letter-annotation dictionary as a simple list of integers:

      >>> print(record.letter_annotations["phred_quality"])
      [26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 24, 26, 22, 26, 26, 13, 22, 26, 18, 24, 18, 18, 18, 18]

  If you have access to data as a FASTQ format file, using that directly would be simpler and more straight forward. Note that you can easily use this function to convert paired FASTA and QUAL files into FASTQ files:

      >>> from Bio import SeqIO
      >>> with open("Quality/example.fasta") as f:
      ...     with open("Quality/example.qual") as q:
      ...         SeqIO.write(PairedFastaQualIterator(f, q), "Quality/temp.fastq", "fastq")
      ...
      3

  And don’t forget to clean up the temp file if you don’t need it anymore:

      >>> import os
      >>> os.remove("Quality/temp.fastq")

exception Bio.SeqIO.QualityIO.InvalidCharError(full_string: str, index: int, details: str, r: int = 3)

  Bases: `ValueError`

  Custom error for strings that have a character that is invalid for whatever reason (eg: non-ascii, invalid range)

  Main attributes:

    - full_string - the string which contains the invalid character (str)

    - index - position of the invalid character in full_string (int)

    - details - additional information to add to the error message. Like: ‘not in correct range’ (str)

    - r - how many characters on each side of the invalid character to include in the error message (int)

  full_string: str
  index: int
  details: str
  r: int = 3
  __str__() → str

    Return str(self).

  __annotations__ = {'details': <class 'str'>, 'full_string': <class 'str'>, 'index': <class 'int'>, 'r': <class 'int'>}
  __dataclass_fields__ = {'details': Field(name='details',type=<class 'str'>,default=<dataclasses._MISSING_TYPE object>,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'full_string': Field(name='full_string',type=<class 'str'>,default=<dataclasses._MISSING_TYPE object>,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'index': Field(name='index',type=<class 'int'>,default=<dataclasses._MISSING_TYPE object>,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'r': Field(name='r',type=<class 'int'>,default=3,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD)}
  __dataclass_params__ = _DataclassParams(init=True,repr=True,eq=True,order=False,unsafe_hash=False,frozen=False,match_args=True,kw_only=False,slots=False,weakref_slot=False)
  __eq__(other)

    Return self==value.

  __firstlineno__ = 2484
  __hash__ = None
  __init__(full_string: str, index: int, details: str, r: int = 3) → None
  __match_args__ = ('full_string', 'index', 'details', 'r')
  __replace__(**changes)
  __repr__()

    Return repr(self).

  __static_attributes__ = ()

Biopython v: 1.85

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