Man pages for metaX
An R package for metabolomic data analysis

addIdentInfoAdd identification result into metaXpara object
addValueNormaddValueNorm
autoRemoveOutlierAutomatically detect outlier samples
bootPLSDAFit predictive models for PLS-DA
calcAUROCClassical univariate ROC analysis
calcVIPCalculate the VIP for PLS-DA
centercenter
checkPvaluePlotcheckPvaluePlot
checkQCPlotcheckQCPlot
cor.networkCorrelation network analysis
createModelsCreate predictive models
dataCleandataClean
dir.casedir.case
dir.ctrldir.ctrl
doQCRLSCUsing the QC samples to do the quality control-robust spline...
featureSelectionFeature selection and modeling
filterPeaksfilterPeaks
filterQCPeaksfilterQCPeaks
filterQCPeaksByCVFilter peaks according to the RSD of peaks in QC samples
getPeaksTableGet a data.frame which contained the peaksData in metaXpara
group.bwgroup.bw
group.bw0group.bw0
group.maxgroup.max
group.minfracgroup.minfrac
group.minsampgroup.minsamp
group.mzwidgroup.mzwid
group.mzwid0group.mzwid0
group.sleepgroup.sleep
hasQCJudge whether the data has QC samples
idresidres
importDataFromMetaboAnalystimportDataFromMetaboAnalyst
importDataFromQIimportDataFromQI
importDataFromXCMSimportDataFromXCMS
kfoldkfold
makeDirectoryCreate directory
makeMetaboAnalystInputExport a csv file which can be used for MetaboAnalyst
metaboliteAnnotationMetabolite identification
metaXpara-classAn S4 class to represent the parameters and data for data...
metaXpipemetaXpipe
methodmethod
missingValueImputeMissing value imputation
missValueImputeMethodmissValueImputeMethod
myCalcAUROCClassical univariate ROC analysis
myPLSDAPerform PLS-DA analysis
ncompncomp
normalizeNormalisation of peak intensity
npermnperm
outdiroutdir
pathwayAnalysisPathway analysis
peakFinderPeak detection by using XCMS package
peaksDatapeaksData
peakStatDo the univariate and multivariate statistical analysis
permutePLSDApermutePLSDA
plotCorHeatmapPlot correlation heatmap
plotCVPlot the CV distribution of peaks in each group
plotHeatMapPlot heatmap
plotIntDistrPlot the distribution of the peaks intensity
plotLoadingPlot figures for PCA/PLS-DA loadings
plotMissValuePlot missing value distribution
plotNetworkPlot correlation network map
plotPCAPlot PCA figure
plotPeakBoxPlot boxplot for each feature
plotPeakNumberPlot the distribution of the peaks number
plotPeakSNPlot the distribution of the peaks S/N
plotPeakSumDistPlot the total peak intensity distribution
plotPLSDAPlot PLS-DA figure
plotQCPlot the correlation change of the QC samples.
plotQCRLSCPlot figures for QC-RLSC
plotTreeMapPlot Phylogenies for samples
plsDAPara-classAn S4 class to represent the parameters for PLS-DA analysis
powerAnalystPower Analysis
prefixprefix
preProcessPre-Processing
qcRlscSpanqcRlscSpan
ratioPairsratioPairs
rawPeaksrawPeaks
removeSampleRemove samples from the metaXpara object
reSetPeaksDatareSetPeaksData
retcor.methodretcor.method
retcor.plottyperetcor.plottype
retcor.profStepretcor.profStep
runPLSDArunPLSDA
sampleListFilesampleListFile
scalescale
selectBestComponentSelect the best component for PLS-DA
tt
transformationData transformation
validationvalidation
xcmsSet.fitgaussxcmsSet.fitgauss
xcmsSet.fwhmxcmsSet.fwhm
xcmsSet.integratexcmsSet.integrate
xcmsSet.maxxcmsSet.max
xcmsSet.methodxcmsSet.method
xcmsSet.mzCenterFunxcmsSet.mzCenterFun
xcmsSet.mzdiffxcmsSet.mzdiff
xcmsSet.noisexcmsSet.noise
xcmsSet.nSlavesxcmsSet.nSlaves
xcmsSetObjxcmsSetObj
xcmsSet.peakwidthxcmsSet.peakwidth
xcmsSet.polarityxcmsSet.polarity
xcmsSet.ppmxcmsSet.ppm
xcmsSet.prefilterxcmsSet.prefilter
xcmsSet.profparamxcmsSet.profparam
xcmsSet.sleepxcmsSet.sleep
xcmsSet.snthreshxcmsSet.snthresh
xcmsSet.stepxcmsSet.step
xcmsSet.verbose.columnsxcmsSet.verbose.columns
zero2NAConvert the value <=0 to NA
metaX documentation built on Oct. 5, 2016, 4:41 a.m.