Statistical analysis for sparse high-throughput sequencing


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Documentation for package ‘metagenomeSeq’ version 1.40.0

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

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
fitFeatureModelResults-class Class "fitFeatureModelResults" - a formal class for storing results from a fitFeatureModel call
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.
fitZigResults-class Class "fitZigResults" - a formal class for storing results from a fitZig call

-- 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
MRihw MRihw runs IHW within a MRcoefs() call
MRihw-method MRihw runs IHW within a MRcoefs() call
MRihw-method MRihw runs IHW within a MRcoefs() call
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

-- W --

wrenchNorm Computes normalization factors using wrench instead of cumNorm

-- Z --

zigControl Settings for the fitZig function

-- misc --

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