Package 'metagenomeSeq' - Bioconductor

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22 isItStillActivegetZCalculate the current Z estimate responsibilities (posterior probabilities)DescriptionCalculate the current Z estimate responsibilities (posterior probabilities)UsagegetZ(z, zUsed, stillActive, nll, nllUSED)ArgumentszzUsedstillActivenllnllUSEDMatrix (m x n) of estimate responsibilities (probabilities that a count comes froma spike distribution at 0).Matrix (m x n) of estimate responsibilities (probabilities that a count comes froma spike distribution at 0) that are actually used (following convergence).A vector of size M booleans saying if a feature is still active or not.Vector of size M with the current negative log-likelihoods.Vector of size M with the converged negative log-likelihoods.ValueA list of updated zUsed and nllUSED.See AlsofitZigisItStillActiveFunction to determine if a feature is still active.DescriptionIn the Expectation Maximization routine features posterior probabilities routinely converge basedon a tolerance threshold. This function checks whether or not the feature’s negative log-likelihood(measure of the fit) has changed or not.UsageisItStillActive(eps, tol, stillActive, stillActiveNLL, nll)
libSize 23ArgumentsepstolstillActiveVector of size M (features) representing the relative difference between the newnll and old nll.The threshold tolerance for the differenceA vector of size M booleans saying if a feature is still active or not.stillActiveNLL A vector of size M recording the negative log-likelihoods of the various features,updated for those still active.nllVector of size M with the current negative log-likelihoods.ValueNone.See AlsofitZiglibSizeAccess sample depth of coverage from MRexperiment objectDescriptionThe libSize vector represents the column (sample specific) sums of features, i.e. the total numberof reads for a sample or depth of coverage. It is used by fitZig.UsagelibSize(obj)Argumentsobja MRexperiment object.Author(s)Joseph N. Paulson, jpaulson@umiacs.umd.eduExamplesdata(lungData)head(libSize(lungData))
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: getPi 21ArgumentszMatrix (m x n) of
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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