Package: metabolyseR 0.15.4

Jasen Finch

metabolyseR: Methods for Pre-Treatment, Data Mining and Correlation Analyses of Metabolomics Data

A tool kit for pre-treatment, modelling, feature selection and correlation analyses of metabolomics data.

Authors:Jasen Finch [aut, cre]

metabolyseR_0.15.4.tar.gz
metabolyseR_0.15.4.zip(r-4.7)metabolyseR_0.15.4.zip(r-4.6)metabolyseR_0.15.4.zip(r-4.5)
metabolyseR_0.15.4.tgz(r-4.6-any)metabolyseR_0.15.4.tgz(r-4.5-any)
metabolyseR_0.15.4.tar.gz(r-4.7-any)metabolyseR_0.15.4.tar.gz(r-4.6-any)
metabolyseR_0.15.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
metabolyseR/json (API)

# Install 'metabolyseR' in R:
install.packages('metabolyseR', repos = c('https://aberhrml.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/jasenfinch/metabolyser/issues

Pkgdown/docs site:https://jasenfinch.github.io

On CRAN:

Conda:

metabolomics

3.78 score 1 packages 7 scripts 103 exports 102 dependencies

Last updated from:08bb28b7d2. Checks:7 ERROR, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64ERROR361
source / vignettesOK388
linux-release-x86_64ERROR338
macos-release-arm64ERROR263
macos-oldrel-arm64ERROR224
windows-develERROR330
windows-releaseERROR317
windows-oldrelERROR304
wasm-releaseOK158

Exports:%>%aggregateMeanaggregateMedianaggregateSumanalysisDataanalysisElementsanalysisParametersanalysisResultsanovabinaryComparisonsbindRowschangeParameter<-clsAddclsArrangeclsAvailableclsExtractclsRemoveclsRenameclsReplacecorrectionCentercorrelationscorrelationsParametersdatdat<-explanatoryFeaturesexportParametersfeaturesimportanceimportanceMetricsimputeAllimputeClasskeepClasseskeepFeatureskeepSampleslinearRegressionmdsmetabolysemetricsmodellingMethodsmodellingParametersmtrynFeaturesnSamplesoccupancyoccupancyMaximumoccupancyMinimumparametersparameters<-parseParametersplanplotExplanatoryHeatmapplotFeatureplotImportanceplotLDAplotMDSplotMetricsplotOccupancyplotPCAplotROCplotRSDplotSupervisedRFplotTICplotUnsupervisedRFpredictpredictionspreTreatedpreTreated<-preTreatmentElementspreTreatmentMethodspreTreatmentParametersproximityQCimputeQCoccupancyQCremoveQCrsdFilterrandomForestrawraw<-reAnalyseremoveClassesremoveFeaturesremoveSamplesresponserocrsdsinfosinfo<-splittransformArcSinetransformAutotransformCentertransformLeveltransformLntransformLog10transformParetotransformPercenttransformRangetransformSQRTtransformTICnormtransformVastttesttunetype

Dependencies:backportsbase64encbroombslibcachemcheckmateclasscliclustercodetoolscolorspacecpp11crayondata.tabledigestdoFuturedoRNGdplyre1071evaluatefarverfastmapfontawesomeforeachforeignforestControlFormulafsfurrrfuturefuture.applygenericsggdendroggplot2ggrepelggthemesglobalsgluegridExtragtablehardhathighrHmischtmlTablehtmltoolshtmlwidgetsisobanditeratorsitertoolsjquerylibjsonliteknitrlabelinglatticelifecyclelistenvlubridatemagrittrMASSMatrixmemoisemimemissForestnnetparallellypatchworkpillarpkgconfigproxypurrrR6randomForestrangerrappdirsrbibutilsRColorBrewerRcppRcppEigenRdpackrlangrmarkdownrngtoolsrpartrstudioapiS7sassscalessparsevctrsstringistringrtibbletidyrtidyselecttimechangetinytexutf8vctrsviridisLitewithrxfunyamlyardstick

Metabolomics data pre-treatment
Introduction | Example data | Parallel processing | Pre-treatment elements | Removal of samples, classes or features | Keeping samples, classes or features | Feature filtering based on occupancy | Data transformation | Sample aggregation | Batch/block correction | Imputation of missing data | Feature filtering based on quality control (QC) samples | Routine analyses
Rendered frompre_treatment.Rmdusingknitr::rmarkdown

Last update: 2023-09-12
Started: 2021-04-16

Quick start example analysis
Rendered fromquick_start.Rmdusingknitr::rmarkdown

Last update: 2023-08-14
Started: 2021-04-16

Modelling and feature selection
Introduction | Example data | Parallel processing | Random Forest | Unsupervised | Classification | Multinomial comparisons | Binary comparisons | Regression | Univariate analyses | Welch's t-test | ANOVA | Linear regression | Routine analyses
Rendered frommodelling.Rmdusingknitr::rmarkdown

Last update: 2023-02-20
Started: 2021-04-16

Introduction
Parallel processing | Exploratory analyses | Analysis data | Sample information | Keeping / removing samples or features | Routine analyses | Analysis parameters | Programatic specification | YAML specification | Performing an analysis | Performing a re-analysis | Extracting analysis results
Rendered frommetabolyseR.Rmdusingknitr::rmarkdown

Last update: 2021-09-14
Started: 2021-09-14

Readme and manuals

Help Manual

Help pageTopics
Sample aggregationaggregateMean aggregateMean,AnalysisData-method aggregateMedian aggregateMedian,AnalysisData-method aggregateSum aggregateSum,AnalysisData-method
Analysis S4 classAnalysis-class
AnalysisData class constructoranalysisData
AnalysisData S4 classAnalysisData-class
Analysis elementsanalysisElements
Create an 'AnalysisParameters' S4 class objectanalysisParameters
AnalysisParameters S4 classAnalysisParameters-class
ANOVAanova anova,AnalysisData-method
Modelling accessor methodsbinaryComparisons binaryComparisons,AnalysisData-method explanatoryFeatures explanatoryFeatures,Analysis-method explanatoryFeatures,list-method explanatoryFeatures,RandomForest-method explanatoryFeatures,Univariate-method importance importance,Analysis-method importance,list-method importance,RandomForest-method importance,Univariate-method importanceMetrics importanceMetrics,RandomForest-method metrics metrics,Analysis-method metrics,list-method metrics,RandomForest-method mtry mtry,AnalysisData-method predictions predictions,Analysis-method predictions,list-method predictions,RandomForest-method proximity proximity,Analysis-method proximity,list-method proximity,RandomForest-method response response,RandomForest-method response,Univariate-method type type,RandomForest-method type,Univariate-method
Bind 'AnalysisData' objects by rowbindRows bindRows,list-method
Change analysis parameterschangeParameter<- changeParameter<-,AnalysisParameters-method
Sample meta information wranglingclsAdd clsAdd,Analysis-method clsAdd,AnalysisData-method clsArrange clsArrange,Analysis-method clsArrange,AnalysisData-method clsAvailable clsAvailable,Analysis-method clsAvailable,AnalysisData-method clsExtract clsExtract,Analysis-method clsExtract,AnalysisData-method clsRemove clsRemove,Analysis-method clsRemove,AnalysisData-method clsRename clsRename,Analysis-method clsRename,AnalysisData-method clsReplace clsReplace,Analysis-method clsReplace,AnalysisData-method
Batch/block correctioncorrectionCenter correctionCenter,AnalysisData-method
Feature correlation analysiscorrelations correlations,Analysis-method correlations,AnalysisData-method
Correlations parameterscorrelationsParameters
'AnalysisData' and 'Analysis' class accessorsanalysisResults analysisResults,Analysis-method dat dat,Analysis-method dat,AnalysisData-method dat<- dat<-,Analysis-method dat<-,AnalysisData-method features features,Analysis-method features,AnalysisData-method nFeatures nFeatures,Analysis-method nFeatures,AnalysisData-method nSamples nSamples,Analysis-method nSamples,AnalysisData-method preTreated preTreated,Analysis-method preTreated<- preTreated<-,Analysis-method raw raw,Analysis-method raw<- raw<-,Analysis-method sinfo sinfo,Analysis-method sinfo,AnalysisData-method sinfo<- sinfo<-,Analysis-method sinfo<-,AnalysisData-method
Missing data imputationimputeAll imputeAll,AnalysisData-method imputeClass imputeClass,AnalysisData-method
Keep samples, classes or featureskeepClasses keepClasses,AnalysisData-method keepFeatures keepFeatures,AnalysisData-method keepSamples keepSamples,AnalysisData-method
Linear regressionlinearRegression linearRegression,AnalysisData-method
Multidimensional scaling (MDS)mds mds,Analysis-method mds,list-method mds,RandomForest-method
Perform an analysismetabolyse reAnalyse reAnalyse,Analysis-method
Modelling parametersmodellingMethods modellingParameters
Calculate feature class occupanciesoccupancy occupancy,AnalysisData-method
Feature occupancy filteringoccupancyMaximum occupancyMaximum,AnalysisData-method occupancyMinimum occupancyMinimum,AnalysisData-method
Get or set analysis parametersparameters parameters,Analysis-method parameters,AnalysisParameters-method parameters<- parameters<-,Analysis-method parameters<-,AnalysisParameters-method
Parse/export analysis parametersexportParameters exportParameters,Analysis-method exportParameters,AnalysisParameters-method parseParameters
Heatmap plot of explantory featuresplotExplanatoryHeatmap plotExplanatoryHeatmap,Analysis-method plotExplanatoryHeatmap,list-method plotExplanatoryHeatmap,RandomForest-method plotExplanatoryHeatmap,Univariate-method
Plot a featureplotFeature plotFeature,Analysis-method plotFeature,AnalysisData-method
Plot feature importanceplotImportance plotImportance,list-method plotImportance,RandomForest-method plotImportance,Univariate-method
Principle Component - Linear Discriminant Analysis plotplotLDA plotLDA,Analysis-method plotLDA,AnalysisData-method
Multidimensional scaling (MDS) plotplotMDS plotMDS,list-method plotMDS,RandomForest-method
Plot model performance metricsplotMetrics plotMetrics,list-method plotMetrics,RandomForest-method
Plot class occupancy distributionsplotOccupancy plotOccupancy,Analysis-method plotOccupancy,AnalysisData-method
Principle Component Analysis plotplotPCA plotPCA,Analysis-method plotPCA,AnalysisData-method
Plot receiver operator characteristic (ROC) curvesplotROC plotROC,list-method plotROC,RandomForest-method
Plot RSD distributionsplotRSD plotRSD,Analysis-method plotRSD,AnalysisData-method
Supervised random forest MDS plotplotSupervisedRF plotSupervisedRF,Analysis-method plotSupervisedRF,AnalysisData-method
Plot sample total ion countsplotTIC plotTIC,Analysis-method plotTIC,AnalysisData-method
Unsupervised random forest MDS plotplotUnsupervisedRF plotUnsupervisedRF,Analysis-method plotUnsupervisedRF,AnalysisData-method
Predict random forest model responsespredict predict,RandomForest,AnalysisData-method
Pre-treatment parameterspreTreatmentElements preTreatmentMethods preTreatmentParameters
Quality control (QC) sample treatmentsQCimpute QCimpute,AnalysisData-method QCoccupancy QCoccupancy,AnalysisData-method QCremove QCremove,AnalysisData-method QCrsdFilter QCrsdFilter,AnalysisData-method
Random forestrandomForest randomForest,AnalysisData-method
RandomForest S4 classRandomForest-class
Remove samples, classes or featuresremoveClasses removeClasses,AnalysisData-method removeFeatures removeFeatures,AnalysisData-method removeSamples removeSamples,AnalysisData-method
Receiver-operator characteristic (ROC) curvesroc roc,Analysis-method roc,list-method roc,RandomForest-method
Calculate feature relative standard deviationsrsd rsd,AnalysisData-method
Split an 'AnalysisData' objectsplit split,AnalysisData-method
Scaling, transformation and normalisation methodstransformArcSine transformArcSine,AnalysisData-method transformAuto transformAuto,AnalysisData-method transformCenter transformCenter,AnalysisData-method transformLevel transformLevel,AnalysisData-method transformLn transformLn,AnalysisData-method transformLog10 transformLog10,AnalysisData-method transformPareto transformPareto,AnalysisData-method transformPercent transformPercent,AnalysisData-method transformRange transformRange,AnalysisData-method transformSQRT transformSQRT,AnalysisData-method transformTICnorm transformTICnorm,AnalysisData-method transformVast transformVast,AnalysisData-method
Welch's t-testttest ttest,AnalysisData-method
Tune random forest parameterstune tune,AnalysisData-method
Univariate S4 classUnivariate-class