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Individualized Multi-Omic Pathway Deviation Scores Using Multiple Factor Analysis

Bioconductor version: Release (3.19)

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.

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

Maintainer: Andrea Rau <andrea.rau at>

Citation (from within R, enter citation("padma")):


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Reference Manual PDF


biocViews BioCarta, GeneExpression, MethylSeq, Pathways, PrincipalComponent, RNASeq, Software, StatisticalMethod
Version 1.14.1
In Bioconductor since BioC 3.12 (R-4.0) (3.5 years)
License GPL (>=3)
Depends R (>= 4.1.0), SummarizedExperiment, S4Vectors
Imports FactoMineR, MultiAssayExperiment, methods, graphics, stats, utils
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Suggests testthat, BiocStyle, knitr, rmarkdown, KEGGREST, missMDA, ggplot2, ggrepel, car, cowplot, reshape2
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