Package: pathMED 1.4.0
Jordi Martorell-Marugán
pathMED: Scoring Personalized Molecular Portraits
PathMED is a collection of tools to facilitate precision medicine studies with omics data (e.g. transcriptomics). Among its funcionalities, genesets scores for individual samples may be calculated with several methods. These scores may be used to train machine learning models and to predict clinical features on new data. For this, several machine learning methods are evaluated in order to select the best method based on internal validation and to tune the hyperparameters. Performance metrics and a ready-to-use model to predict the outcomes for new patients are returned.
Authors:
pathMED_1.4.0.tar.gz
pathMED_1.4.0.zip(r-4.7)pathMED_1.4.0.zip(r-4.6)pathMED_1.4.0.zip(r-4.5)
pathMED_1.4.0.tgz(r-4.6-any)pathMED_1.4.0.tgz(r-4.5-any)
pathMED_1.4.0.tar.gz(r-4.7-any)pathMED_1.4.0.tar.gz(r-4.6-any)
pathMED_1.4.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
pathMED/json (API)
| # Install 'pathMED' in R: |
| install.packages('pathMED', repos = c('https://bioc-release.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/jordimartorell/pathmed/issues
- genesetsData - Preloaded gene sets
- pathMEDExampleData - Example of test gene expression data
- pathMEDExampleMetadata - Metadata of test gene expression data
- refData - Example of reference gene expression datasets
On BioConductor:pathMED-1.5.0(bioc 3.24)pathMED-1.4.0(bioc 3.23)
pathwaysclassificationfeatureextractiontranscriptomics
Last updated from:f76aa44d79 (on RELEASE_3_23). Checks:1 WARNING, 7 OK, 2 ERROR. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | WARNING | 204 | ||
| linux-devel-x86_64 | OK | 479 | ||
| source / vignettes | OK | 357 | ||
| linux-release-x86_64 | OK | 442 | ||
| macos-release-arm64 | ERROR | 240 | ||
| macos-oldrel-arm64 | ERROR | 178 | ||
| windows-devel | OK | 312 | ||
| windows-release | OK | 331 | ||
| windows-oldrel | OK | 357 | ||
| wasm-release | OK | 219 |
Exports:ann2termbuildRefObjectdissectDBgetScoresmethodsMLmScores_createReferencemScores_filterPathsmScores_imputeFromReferencepredictExternaltrainModel
Dependencies:abindannotateAnnotationDbiaskpassassortheadbackportsbase64encbeachmatBHBiobaseBiocFileCacheBiocGenericsbiocmakeBiocParallelBiocSingularBiostringsbitbit64blobbootbroombslibcachemcarcarDatacaretcaretEnsembleclasscliclockclustercodetoolscolorspacecorrplotcowplotcpp11crayoncrosstalkcurldata.tableDBIdbplyrdecoupleRDelayedArrayDelayedMatrixStatsdendextendDerivdiagramdigestdir.expirydoBydplyrDTe1071edgeRellipseemmeansenergyestimabilityevaluatefactoextraFactoMineRfarverfastmapfilelockflashClustfontawesomeforeachforecastformatRFormulafracdifffsfutile.loggerfutile.optionsfuturefuture.applygenericsGenomicRangesggplot2ggppggpubrggrepelggsciggsignifglobalsgluegowergraphgridExtraGSEABasegslGSVAgtableh5mreadhardhatHDF5Arrayhighrhtmltoolshtmlwidgetshttrhttr2ipredIRangesirlbaisobanditeratorsjquerylibjsonliteKEGGRESTKernSmoothknitrlabelinglambda.rlaterlatticelavalazyevalleapslifecyclelimmalistenvlme4lmtestlocfitlubridatemagickmagrittrMASSMatrixMatrixGenericsMatrixModelsmatrixStatsmemoisememusemetricamgcvmicrobenchmarkmimeminervaminqaModelMetricsmodelrmultcompViewmvtnormnlmenloptrnnetnumDerivopensslotelparallellypatchworkpbapplypbkrtestpillarpkgconfigplotlyplyrpngpolynompROCprodlimprogressrpromisesproxypurrrquantregR6rappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackrecipesreformulasreshapereshape2rhdf5rhdf5filtersRhdf5librjsonrlangrmarkdownrpartRSQLiterstatixrsvdS4ArraysS4VectorsS7sassScaledMatrixscalesscatterplot3dSeqinfoshapeSingleCellExperimentsingscoresnowSparseArraySparseMsparseMatrixStatssparsevctrsSpatialExperimentSQUAREMstatmodstringistringrSummarizedExperimentsurvivalsystibbletidyrtidyselecttimechangetimeDatetinytextzdburcautf8vctrsviridisviridisLitewithrxfunXMLxtablextsXVectoryamlzoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Annotate the pathways from a scores matrix | ann2term |
| Create a reference data object for input to the pathMED functions | buildRefObject |
| Split pathways into coexpressed subpathways | dissectDB |
| Preloaded gene sets | genesetsData |
| Calculate pathways scores for a dataset | getScores |
| Prepare the models parameter for the trainModel function | methodsML |
| Create a reference dataset based on M-scores | mScores_createReference |
| Filter pathways from the reference M-scores dataset | mScores_filterPaths |
| Estimate M-scores for a dataset without healthy controls | mScores_imputeFromReference |
| Example of test gene expression data | pathMEDExampleData |
| Metadata of test gene expression data | pathMEDExampleMetadata |
| Predict conditions in external datasets | predictExternal |
| Example of reference gene expression datasets | refData |
| Train ML models and perform internal validation | trainModel |
