Package 'metagenomeSeq' - Bioconductor

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16 fitDOfitDOWrapper to calculate Discovery Odds Ratios on feature values.DescriptionThis function returns a data frame of p-values, odds ratios, lower and upper confidence limits forevery row of a matrix. The discovery odds ratio is calculated as using Fisher’s exact test on actualcounts. The test’s hypothesis is whether or not the discovery of counts for a feature (of all counts)is found in greater proportion in a particular group.UsagefitDO(obj, cl, norm = TRUE, log = TRUE)ArgumentsobjclnormlogA MRexperiment object with a count matrix, or a simple count matrix.Group comparisonWhether or not to normalize the counts - if MRexperiment object.Whether or not to log2 transform the counts - if MRexperiment object.ValueNASee AlsocumNorm fitZigExamplesdata(lungData)k = grep("Extraction.Control",pData(lungData)$SampleType)lungTrim = lungData[,-k]lungTrim = lungTrim[-which(rowSums(MRcounts(lungTrim)>0)
fitMeta 17fitMetaComputes a slightly modified form of Metastats.DescriptionUsageWrapper to perform the permutation test on the t-statistic. This is the original method employedby metastats (for non-sparse large samples). We include CSS normalization though (optional) andlog2 transform the data. In this method the null distribution is not assumed to be a t-dist.fitMeta(obj, mod, useCSSoffset = TRUE, B = 1000, coef = 2, sl = 1000)ArgumentsobjmoduseCSSoffsetBcoefslA MRexperiment object with count data.The model for the count distribution.Boolean, whether to include the default scaling parameters in the model or not.Number of permutations.The coefficient of interest.The value to scale by (default=1000).ValueCall made, fit object from lmFit, t-statistics and p-values for each feature.fitPAWrapper to run fisher’s test on presence/absence of a feature.DescriptionUsageThis function returns a data frame of p-values, odds ratios, lower and upper confidence limits forevery row of a matrix.fitPA(obj, cl, thres = 0)ArgumentsobjclthresA MRexperiment object with a count matrix, or a simple count matrix.Group comparisonThreshold for defining presence/absence.
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: filterData 15Author(s)Joseph N. Pau
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 and 28: makeLabels 27Referenceshttp://www.n
Page 29 and 30: MRcounts 29Examplesdata(lungData)k
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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