# Statistical analysis for sparse high-throughput sequencing

## Documentation for package ‘metagenomeSeq’ version 1.20.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

A B C D E F G I L M N P Q R S T U Z misc

metagenomeSeq-deprecated-package | Depcrecated functions in the metagenomeSeq package.
metagenomeSeq-package | Statistical analysis for sparse high-throughput sequencing

## -- A --

aggregateBySample | Aggregates a MRexperiment object or counts matrix to by a factor.
aggregateByTaxonomy | Aggregates a MRexperiment object or counts matrix to a particular level.
aggSamp | Aggregates a MRexperiment object or counts matrix to by a factor.
aggTax | Aggregates a MRexperiment object or counts matrix to a particular level.

## -- B --

biom2MRexperiment | Biom to MRexperiment objects

## -- C --

calcNormFactors | Cumulative sum scaling (css) normalization factors
calcPosComponent | Positive component
calcShrinkParameters | Calculate shrinkage parameters
calcStandardError | Calculate the zero-inflated log-normal statistic's standard error
calculateEffectiveSamples | Estimated effective samples per feature
calcZeroAdjustment | Calculate the zero-inflated component's adjustment factor
calcZeroComponent | Zero component
colMeans-method | Class "MRexperiment" - a modified eSet object for the data from high-throughput sequencing experiments
colSums-method | Class "MRexperiment" - a modified eSet object for the data from high-throughput sequencing experiments
correctIndices | Calculate the correct indices for the output of correlationTest
correlationTest | Correlation of each row of a matrix or MRexperiment object
corTest | Correlation of each row of a matrix or MRexperiment object
cumNorm | Cumulative sum scaling normalization
cumNormMat | Cumulative sum scaling factors.
cumNormStat | Cumulative sum scaling percentile selection
cumNormStatFast | Cumulative sum scaling percentile selection

## -- D --

deprecated_metagenomeSeq_function | Depcrecated functions in the metagenomeSeq package.
doCountMStep | Compute the Maximization step calculation for features still active.
doEStep | Compute the Expectation step.
doZeroMStep | Compute the zero Maximization step.

## -- E --

exportMat | Export the normalized MRexperiment dataset as a matrix.
exportMatrix | Export the normalized MRexperiment dataset as a matrix.
exportStats | Various statistics of the count data.
expSummary | Access MRexperiment object experiment data
expSummary-method | Access MRexperiment object experiment data
extractMR | Extract the essentials of an MRexperiment.

## -- F --

filterData | Filter datasets according to no. features present in features with at least a certain depth.
fitDO | Wrapper to calculate Discovery Odds Ratios on feature values.
fitFeatureModel | Computes differential abundance analysis using a zero-inflated log-normal model
fitLogNormal | Computes a log-normal linear model and permutation based p-values.
fitMeta | Depcrecated functions in the metagenomeSeq package.
fitMultipleTimeSeries | Discover differentially abundant time intervals for all bacteria
fitPA | Wrapper to run fisher's test on presence/absence of a feature.
fitSSTimeSeries | Discover differentially abundant time intervals using SS-Anova
fitTimeSeries | Discover differentially abundant time intervals
fitZeroLogNormal | Compute the log fold-change estimates for the zero-inflated log-normal model
fitZig | Computes the weighted fold-change estimates and t-statistics.

## -- G --

genusPlot | Basic plot function of the raw or normalized data.
getCountDensity | Compute the value of the count density function from the count model residuals.
getEpsilon | Calculate the relative difference between iterations of the negative log-likelihoods.
getNegativeLogLikelihoods | Calculate the negative log-likelihoods for the various features given the residuals.
getPi | Calculate the mixture proportions from the zero model / spike mass model residuals.
getZ | Calculate the current Z estimate responsibilities (posterior probabilities)

## -- I --

isItStillActive | Function to determine if a feature is still active.

## -- L --

libSize | Access sample depth of coverage from MRexperiment object
libSize-method | Class "MRexperiment" - a modified eSet object for the data from high-throughput sequencing experiments
libSize<- | Replace the library sizes in a MRexperiment object
libSize<--method | Replace the library sizes in a MRexperiment object
loadBiom | Load objects organized in the Biom format.
loadMeta | Load a count dataset associated with a study.
loadMetaQ | Load a count dataset associated with a study set up in a Qiime format.
loadPhenoData | Load a clinical/phenotypic dataset associated with a study.
load_biom | Depcrecated functions in the metagenomeSeq package.
load_meta | Depcrecated functions in the metagenomeSeq package.
load_metaQ | Depcrecated functions in the metagenomeSeq package.
load_phenoData | Depcrecated functions in the metagenomeSeq package.
lungData | OTU abundance matrix of samples from a smoker/non-smoker study

## -- M --

makeLabels | Function to make labels simpler
mergeMRexperiments | Merge two MRexperiment objects together
mergeTable | Merge two tables
metagenomeSeq | Statistical analysis for sparse high-throughput sequencing
metagenomeSeq-deprecated | Depcrecated functions in the metagenomeSeq package.
metagenomicLoader | Load a count dataset associated with a study.
mouseData | OTU abundance matrix of mice samples from a diet longitudinal study
MRcoefs | Table of top-ranked features from fitZig or fitFeatureModel
MRcounts | Accessor for the counts slot of a MRexperiment object
MRcounts-method | Accessor for the counts slot of a MRexperiment object
MRexperiment-class | Class "MRexperiment" - a modified eSet object for the data from high-throughput sequencing experiments
MRexperiment2biom | MRexperiment to biom objects
MRfulltable | Table of top microbial marker gene from linear model fit including sequence information
MRtable | Table of top microbial marker gene from linear model fit including sequence information

## -- N --

newMRexperiment | Create a MRexperiment object
normFactors | Access the normalization factors in a MRexperiment object
normFactors-method | Class "MRexperiment" - a modified eSet object for the data from high-throughput sequencing experiments
normFactors<- | Replace the normalization factors in a MRexperiment object
normFactors<--method | Replace the normalization factors in a MRexperiment object

## -- P --

phenoData | Load a clinical/phenotypic dataset associated with a study.
plotBubble | Basic plot of binned vectors.
plotClassTimeSeries | Plot abundances by class
plotCorr | Basic correlation plot function for normalized or unnormalized counts.
plotFeature | Basic plot function of the raw or normalized data.
plotGenus | Basic plot function of the raw or normalized data.
plotMRheatmap | Basic heatmap plot function for normalized counts.
plotOrd | Plot of either PCA or MDS coordinates for the distances of normalized or unnormalized counts.
plotOTU | Basic plot function of the raw or normalized data.
plotRare | Plot of rarefaction effect
plotTimeSeries | Plot difference function for particular bacteria
posteriorProbs | Access the posterior probabilities that results from analysis
posteriorProbs-method | Access the posterior probabilities that results from analysis

## -- Q --

qiimeLoader | Load a count dataset associated with a study set up in a Qiime format.

## -- R --

returnAppropriateObj | Check if MRexperiment or matrix and return matrix
rowMeans-method | Class "MRexperiment" - a modified eSet object for the data from high-throughput sequencing experiments
rowSums-method | Class "MRexperiment" - a modified eSet object for the data from high-throughput sequencing experiments

## -- S --

settings2 | Settings for the fitZig function
ssFit | smoothing-splines anova fit
ssIntervalCandidate | calculate interesting time intervals
ssPerm | class permutations for smoothing-spline time series analysis
ssPermAnalysis | smoothing-splines anova fits for each permutation

## -- T --

trapz | Trapezoidal Integration
ts2MRexperiment | With a list of fitTimeSeries results, generate an MRexperiment that can be plotted with metavizr

## -- U --

uniqueFeatures | Table of features unique to a group

## -- Z --

zigControl | Settings for the fitZig function

## -- misc --

[-method | Class "MRexperiment" - a modified eSet object for the data from high-throughput sequencing experiments