Statistical analysis for sparse high-throughput sequencing

Documentation for package ‘metagenomeSeq’ version 1.22.0

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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 --

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 --

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 --

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 --

Table of features unique to a group

-- Z --

Settings for the fitZig function

-- misc --

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