A B C D F G H I K M N O P Q R S T V X Z
addIdentInfo | Add identification result into metaXpara object |
addValueNorm<- | addValueNorm |
autoRemoveOutlier | Automatically detect outlier samples |
bootPLSDA | Fit predictive models for PLS-DA |
calcAUROC | Classical univariate ROC analysis |
calcVIP | Calculate the VIP for PLS-DA |
center<- | center |
checkPvaluePlot | checkPvaluePlot |
checkQCPlot | checkQCPlot |
cor.network | Correlation network analysis |
createModels | Create predictive models |
dataClean | dataClean |
dir.case<- | dir.case |
dir.ctrl<- | dir.ctrl |
doQCRLSC | Using the QC samples to do the quality control-robust spline signal correction |
featureSelection | Feature selection and modeling |
filterPeaks | filterPeaks |
filterQCPeaks | filterQCPeaks |
filterQCPeaksByCV | Filter peaks according to the RSD of peaks in QC samples |
getPeaksTable | Get a data.frame which contained the peaksData in metaXpara |
group.bw0<- | group.bw0 |
group.bw<- | group.bw |
group.max<- | group.max |
group.minfrac<- | group.minfrac |
group.minsamp<- | group.minsamp |
group.mzwid0<- | group.mzwid0 |
group.mzwid<- | group.mzwid |
group.sleep<- | group.sleep |
hasQC | Judge whether the data has QC samples |
idres<- | idres |
importDataFromMetaboAnalyst | importDataFromMetaboAnalyst |
importDataFromQI | importDataFromQI |
importDataFromXCMS | importDataFromXCMS |
kfold<- | kfold |
makeDirectory | Create directory |
makeMetaboAnalystInput | Export a csv file which can be used for MetaboAnalyst |
metaboliteAnnotation | Metabolite identification |
metaXpara-class | An S4 class to represent the parameters and data for data processing |
metaXpipe | metaXpipe |
method<- | method |
missingValueImpute | Missing value imputation |
missValueImputeMethod<- | missValueImputeMethod |
myCalcAUROC | Classical univariate ROC analysis |
myPLSDA | Perform PLS-DA analysis |
ncomp<- | ncomp |
normalize | Normalisation of peak intensity |
nperm<- | nperm |
outdir<- | outdir |
pathwayAnalysis | Pathway analysis |
peakFinder | Peak detection by using XCMS package |
peaksData<- | peaksData |
peakStat | Do the univariate and multivariate statistical analysis |
permutePLSDA | permutePLSDA |
plotCorHeatmap | Plot correlation heatmap |
plotCV | Plot the CV distribution of peaks in each group |
plotHeatMap | Plot heatmap |
plotIntDistr | Plot the distribution of the peaks intensity |
plotLoading | Plot figures for PCA/PLS-DA loadings |
plotMissValue | Plot missing value distribution |
plotNetwork | Plot correlation network map |
plotPCA | Plot PCA figure |
plotPeakBox | Plot boxplot for each feature |
plotPeakNumber | Plot the distribution of the peaks number |
plotPeakSN | Plot the distribution of the peaks S/N |
plotPeakSumDist | Plot the total peak intensity distribution |
plotPLSDA | Plot PLS-DA figure |
plotQC | Plot the correlation change of the QC samples. |
plotQCRLSC | Plot figures for QC-RLSC |
plotTreeMap | Plot Phylogenies for samples |
plsDAPara-class | An S4 class to represent the parameters for PLS-DA analysis |
powerAnalyst | Power Analysis |
prefix<- | prefix |
preProcess | Pre-Processing |
qcRlscSpan<- | qcRlscSpan |
ratioPairs<- | ratioPairs |
rawPeaks<- | rawPeaks |
removeSample | Remove samples from the metaXpara object |
reSetPeaksData | reSetPeaksData |
retcor.method<- | retcor.method |
retcor.plottype<- | retcor.plottype |
retcor.profStep<- | retcor.profStep |
runPLSDA | runPLSDA |
sampleListFile<- | sampleListFile |
scale<- | scale |
selectBestComponent | Select the best component for PLS-DA |
t<- | t |
transformation | Data transformation |
validation<- | validation |
xcmsSet.fitgauss<- | xcmsSet.fitgauss |
xcmsSet.fwhm<- | xcmsSet.fwhm |
xcmsSet.integrate<- | xcmsSet.integrate |
xcmsSet.max<- | xcmsSet.max |
xcmsSet.method<- | xcmsSet.method |
xcmsSet.mzCenterFun<- | xcmsSet.mzCenterFun |
xcmsSet.mzdiff<- | xcmsSet.mzdiff |
xcmsSet.noise<- | xcmsSet.noise |
xcmsSet.nSlaves<- | xcmsSet.nSlaves |
xcmsSet.peakwidth<- | xcmsSet.peakwidth |
xcmsSet.polarity<- | xcmsSet.polarity |
xcmsSet.ppm<- | xcmsSet.ppm |
xcmsSet.prefilter<- | xcmsSet.prefilter |
xcmsSet.profparam<- | xcmsSet.profparam |
xcmsSet.sleep<- | xcmsSet.sleep |
xcmsSet.snthresh<- | xcmsSet.snthresh |
xcmsSet.step<- | xcmsSet.step |
xcmsSet.verbose.columns<- | xcmsSet.verbose.columns |
xcmsSetObj<- | xcmsSetObj |
zero2NA | Convert the value <=0 to NA |