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SCFA

SCFA: Subtyping via Consensus Factor Analysis

Bioconductor version: 3.23 · Package version: 1.22.0

Subtyping via Consensus Factor Analysis (SCFA) can efficiently remove noisy signals from consistent molecular patterns in multi-omics data. SCFA first uses an autoencoder to select only important features and then repeatedly performs factor analysis to represent the data with different numbers of factors. Using these representations, it can reliably identify cancer subtypes and accurately predict risk scores of patients.

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("SCFA")

Details

MaintainerDuc Tran <duct@nevada.unr.edu>
AuthorDuc Tran [aut, cre], Hung Nguyen [aut], Tin Nguyen [fnd]
LicenseLGPL
URLhttps://github.com/duct317/SCFA
Bug Reportshttps://github.com/duct317/SCFA/issues
Downloads rank237
Source branchRELEASE_3_23
biocViewsClassification, Clustering, Software, Survival

Documentation

Download

Dependencies

Depends: R (>= 4.0)

Imports: matrixStats, BiocParallel, torch (>= 0.3.0), coro, igraph, Matrix, cluster, psych, glmnet, RhpcBLASctl, stats, utils, methods, survival

Suggests: knitr, rmarkdown, BiocStyle