Statistical analysis for sparse high-throughput sequencing


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Documentation for package ‘metagenomeSeq’ version 1.6.0

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metagenomeSeq-package Statistical analysis for sparse high-throughput sequencing
aggregateByTaxonomy Aggregates a MRexperiment object or counts matrix to a particular level. Using the featureData information in the MRexperiment, calling aggregateByTaxonomy on a MRexperiment and a particular featureData column (i.e. 'genus') will aggregate counts to the desired level using the aggfun function (default colSums). Possible aggfun alternatives include colMeans and colMedians.
aggTax Aggregates a MRexperiment object or counts matrix to a particular level. Using the featureData information in the MRexperiment, calling aggregateByTaxonomy on a MRexperiment and a particular featureData column (i.e. 'genus') will aggregate counts to the desired level using the aggfun function (default colSums). Possible aggfun alternatives include colMeans and colMedians.
biom2MRexperiment Biome to MRexperiment objects
calculateEffectiveSamples Estimated effective samples per feature
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 Pairwise correlation for each row of a matrix or MRexperiment object
corTest Pairwise correlation for each row of a matrix or MRexperiment object
cumNorm Cumulative sum scaling factors.
cumNormMat Cumulative sum scaling factors.
cumNormStat Cumulative sum scaling percentile selection
cumNormStatFast Cumulative sum scaling percentile selection
doCountMStep Compute the Maximization step calculation for features still active.
doEStep Compute the Expectation step.
doZeroMStep Compute the zero Maximization step.
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
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.
fitMeta Computes a slightly modified form of Metastats.
fitPA Wrapper to run fisher's test on presence/absence of a feature.
fitZig Computes the weighted fold-change estimates and t-statistics.
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)
isItStillActive Function to determine if a feature is still active.
libSize Access sample depth of coverage from MRexperiment object
libSize-method Access sample depth of coverage from MRexperiment object
load_biom Load objects organized in the Biome format.
load_meta Load a count dataset associated with a study.
load_metaQ Load a count dataset associated with a study set up in a Qiime format.
load_phenoData Load a clinical/phenotypic dataset associated with a study.
lungData OTU abundance matrix of samples from a smoker/non-smoker study
makeLabels Function to make labels simpler
metagenomeSeq Statistical analysis for sparse high-throughput sequencing
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 microbial marker gene from linear model fit
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
newMRexperiment Create a MRexperiment object
normFactors Access the normalization factors in a MRexperiment object
normFactors-method Access the normalization factors in a MRexperiment object
phenoData Load a clinical/phenotypic dataset associated with a study.
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
posterior.probs Access the posterior probabilities that results from analysis
posterior.probs-method Access the posterior probabilities that results from analysis
qiimeLoader Load a count dataset associated with a study set up in a Qiime format.
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
settings2 Settings for the fitZig function
uniqueFeatures Table of features unique to a group
zigControl Settings for the fitZig function
[-method Class "MRexperiment" - a modified eSet object for the data from high-throughput sequencing experiments