Package 'metagenomeSeq' - Bioconductor

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28 MRcoefsMRcoefsTable of top-ranked microbial marker gene from linear model fitDescriptionExtract a table of the top-ranked features from a linear model fit. This function will be updated soonto provide better flexibility similar to limma’s topTable.UsageMRcoefs(obj, by = 2, coef = NULL, number = 10, taxa = obj$taxa,uniqueNames = FALSE, adjust.method = "fdr", group = 0, eff = 0,numberEff = FALSE, file = NULL)ArgumentsobjbyValuecoefnumbertaxauniqueNamesA list containing the linear model fit produced by lmFit through fitZig.Column number or column name specifying which coefficient or contrast of thelinear model is of interest.Column number(s) or column name(s) specifying which coefficient or contrastof the linear model to display.The number of bacterial features to pick out.Taxa list.Number the various taxa.adjust.method Method to adjust p-values by. Default is "FDR". Options include "holm","hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none". See p.adjustfor more details.groupeffnumberEfffileOne of three choices, 0,1,2,3,4. 0: the sort is ordered by a decreasing absolutevalue coefficient fit. 1: the sort is ordered by the raw coefficient fit in decreasingorder. 2: the sort is ordered by the raw coefficient fit in increasing order. 3:the sort is ordered by the p-value of the coefficient fit in increasing order. 4: nosorting.Restrict samples to have at least a "eff" quantile or number of effective samples.Boolean, whether eff should represent quantile (default/FALSE) or number.Name of output file, including location, to save the table.Table of the top-ranked features determined by the linear fit’s coefficient.See AlsofitZig MRtable
MRcounts 29Examplesdata(lungData)k = grep("Extraction.Control",pData(lungData)$SampleType)lungTrim = lungData[,-k]k = which(rowSums(MRcounts(lungTrim)>0)
Page 1: Package ‘metagenomeSeq’May 22,
Page 5 and 6: calculateEffectiveSamples 5ValueA M
Page 7 and 8: cumNorm 7ArgumentsValueobjmethodalt
Page 9 and 10: cumNormStat 9cumNormStatCumulative
Page 11 and 12: doEStep 11ArgumentszymmCountstillAc
Page 13 and 14: exportMat 13See AlsofitZigexportMat
Page 15 and 16: filterData 15Author(s)Joseph N. Pau
Page 17 and 18: fitMeta 17fitMetaComputes a slightl
Page 19 and 20: getCountDensity 19See AlsocumNorm z
Page 21 and 22: getPi 21ArgumentszMatrix (m x n) of
Page 23 and 24: libSize 23ArgumentsepstolstillActiv
Page 25 and 26: load_metaQ 25ValueA list with objec
Page 27: makeLabels 27Referenceshttp://www.n
Page 31 and 32: MRexperiment2biom 31As mentioned ab
Page 33 and 34: MRtable 33See AlsofitZig MRcoefs MR
Page 35 and 36: normFactors 35ArgumentscountsphenoD
Page 37 and 38: plotFeature 37plotFeatureBasic plot
Page 39 and 40: plotMRheatmap 39Examplesdata(mouseD
Page 41 and 42: plotOTU 41plotOTUBasic plot functio
Page 43 and 44: posterior.probs 43posterior.probsAc
Page 45 and 46: Index∗Topic packagemetagenomeSeq-

Package 'metagenomeSeq' - Bioconductor

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