Package: padma 1.15.1

Andrea Rau

padma: Individualized Multi-Omic Pathway Deviation Scores Using Multiple Factor Analysis

Use multiple factor analysis to calculate individualized pathway-centric scores of deviation with respect to the sampled population based on multi-omic assays (e.g., RNA-seq, copy number alterations, methylation, etc). Graphical and numerical outputs are provided to identify highly aberrant individuals for a particular pathway of interest, as well as the gene and omics drivers of aberrant multi-omic profiles.

Authors:Andrea Rau [cre, aut], Regina Manansala [aut], Florence Jaffrézic [ctb], Denis Laloë [aut], Paul Auer [aut]

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padma.pdf |padma.html
padma/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/andreamrau/padma/issues

Datasets:
  • LUAD_subset - Subset of batch-corrected multi-omic TCGA data in lung adenocarcinoma
  • mirtarbase - Curated miR-target interaction predictions from miRTarBase
  • msigdb - MSigDB canonical pathways and corresponding gene lists

On BioConductor:padma-1.15.0(bioc 3.20)padma-1.14.0(bioc 3.19)

bioconductor-package

11 exports 0.61 score 130 dependencies

Last updated 27 days agofrom:fc1ca8da9d

Exports:factorMapimputed_genesMFA_resultsngenesomicsContribpadmapadmaRunpathway_gene_deviationpathway_nameremoved_genesshow

Dependencies:abindaskpassbackportsbase64encBiobaseBiocBaseUtilsBiocGenericsbootbriobroombslibcachemcallrcarcarDatacliclustercolorspacecpp11crayoncrosstalkcurlDelayedArraydescdiffobjdigestdplyrDTellipseemmeansestimabilityevaluateFactoMineRfansifarverfastmapflashClustfontawesomefsgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2ggrepelgluegtablehighrhtmltoolshtmlwidgetshttpuvhttrIRangesisobandjquerylibjsonliteknitrlabelinglaterlatticelazyevalleapslifecyclelme4magrittrMASSMatrixMatrixGenericsMatrixModelsmatrixStatsmemoisemgcvmimeminqamultcompViewMultiAssayExperimentmunsellmvtnormnlmenloptrnnetnumDerivopensslpbkrtestpillarpkgbuildpkgconfigpkgloadpraiseprocessxpromisespspurrrquantregR6rappdirsRColorBrewerRcppRcppEigenrematch2rlangrmarkdownrprojrootS4ArraysS4Vectorssassscalesscatterplot3dSparseArraySparseMstringistringrSummarizedExperimentsurvivalsystestthattibbletidyrtidyselecttinytexUCSC.utilsutf8vctrsviridisLitewaldowithrxfunXVectoryamlzlibbioc

padma package: Quick-start guide

Rendered frompadma.Rmdusingknitr::rmarkdownon Jun 14 2024.

Last update: 2021-10-14
Started: 2020-01-09

Readme and manuals

Help Manual

Help pageTopics
Plot an MFA factor map for individuals or partial factor map based on padma analysisfactorMap
Subset of batch-corrected multi-omic TCGA data in lung adenocarcinomaLUAD_subset
Curated miR-target interaction predictions from miRTarBasemirtarbase
MSigDB canonical pathways and corresponding gene listsmsigdb
Plot the omics contribution per MFA axis and the overall weighted contributionomicsContrib
Calculate individualized deviation scores from multi-omic datapadma padma,list-method padma,MultiAssayExperiment-method padma-methods
padmaResults object and constructorpadmaResults padmaResults-class
Calculate individualized deviation scores from multi-omic datapadmaRun
Accessors for a padmaResults object.imputed_genes imputed_genes,padmaResults-method MFA_results MFA_results,padmaResults-method ngenes ngenes,padmaResults-method pathway_gene_deviation pathway_gene_deviation,padmaResults-method pathway_gene_deviation-method pathway_name pathway_name,padmaResults-method removed_genes removed_genes,padmaResults-method show show,padmaResults-method
Summarize results from padmasummary summary,padmaResults-method summary-methods