metagenomeSeq is designed to determine features (be it Operational Taxanomic Unit (OTU), species, etc.) that are differentially abundant between two or more groups of multiple samples. metagenomeSeq is designed to address the effects of both normalization and under-sampling of microbial communities on disease association detection and the testing of feature correlations.
|Author||Joseph Nathaniel Paulson, Hisham Talukder, Mihai Pop, Hector Corrada Bravo|
|Date of publication||None|
|Maintainer||Joseph N. Paulson <firstname.lastname@example.org>|
aggregateBySample: Aggregates a MRexperiment object or counts matrix to by a...
aggregateByTaxonomy: Aggregates a MRexperiment object or counts matrix to a...
biom2MRexperiment: Biom to MRexperiment objects
calcNormFactors: Cumulative sum scaling (css) normalization factors
calcPosComponent: Positive component
calcShrinkParameters: Calculate shrinkage parameters
calcStandardError: Calculate the zero-inflated log-normal statistic's standard...
calculateEffectiveSamples: Estimated effective samples per feature
calcZeroAdjustment: Calculate the zero-inflated component's adjustment factor
calcZeroComponent: Zero component
correctIndices: Calculate the correct indices for the output of...
correlationTest: 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
doCountMStep: Compute the Maximization step calculation for features still...
doEStep: Compute the Expectation step.
doZeroMStep: Compute the zero Maximization step.
exportMat: Export the normalized MRexperiment dataset as a matrix.
exportStats: Various statistics of the count data.
expSummary: Access MRexperiment object experiment data
extractMR: Extract the essentials of an MRexperiment.
filterData: Filter datasets according to no. features present in features...
fitDO: Wrapper to calculate Discovery Odds Ratios on feature values.
fitFeatureModel: Computes differential abundance analysis using a...
fitLogNormal: Computes a log-normal linear model and permutation based...
fitMultipleTimeSeries: Discover differentially abundant time intervals for all...
fitPA: Wrapper to run fisher's test on presence/absence of a...
fitSSTimeSeries: Discover differentially abundant time intervals using...
fitTimeSeries: Discover differentially abundant time intervals
fitZeroLogNormal: Compute the log fold-change estimates for the zero-inflated...
fitZig: Computes the weighted fold-change estimates and t-statistics.
getCountDensity: Compute the value of the count density function from the...
getEpsilon: Calculate the relative difference between iterations of the...
getNegativeLogLikelihoods: Calculate the negative log-likelihoods for the various...
getPi: Calculate the mixture proportions from the zero model / spike...
getZ: Calculate the current Z estimate responsibilities (posterior...
isItStillActive: Function to determine if a feature is still active.
libSize: Access sample depth of coverage from MRexperiment object
libSize-set: 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...
loadPhenoData: Load a clinical/phenotypic dataset associated with a study.
lungData: OTU abundance matrix of samples from a smoker/non-smoker...
makeLabels: Function to make labels simpler
mergeMRexperiments: Merge two MRexperiment objects together
mergeTable: Merge two tables
metagenomeSeq-deprecated: Depcrecated functions in the metagenomeSeq package.
metagenomeSeq-package: Statistical analysis for sparse high-throughput sequencing
mouseData: OTU abundance matrix of mice samples from a diet longitudinal...
MRcoefs: Table of top-ranked features from fitZig or fitFeatureModel
MRcounts: Accessor for the counts slot of a MRexperiment object
MRexperiment2biom: MRexperiment to biom objects
MRexperiment-class: Class "MRexperiment" - a modified eSet object for the data...
MRfulltable: Table of top microbial marker gene from linear model fit...
MRtable: Table of top microbial marker gene from linear model fit...
newMRexperiment: Create a MRexperiment object
normFactors: Access the normalization factors in a MRexperiment object
normFactors-set: Replace the normalization factors in a MRexperiment object
plotBubble: Basic plot of binned vectors.
plotClassTimeSeries: Plot abundances by class
plotCorr: Basic correlation plot function for normalized or...
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...
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
returnAppropriateObj: Check if MRexperiment or matrix and return matrix
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
trapz: Trapezoidal Integration
ts2MRexperiment: With a list of fitTimeSeries results, generate an...
uniqueFeatures: Table of features unique to a group
zigControl: Settings for the fitZig function