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SCFA: Subtyping via Consensus Factor Analysis

Bioconductor version: Release (3.18)

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.

Author: Duc Tran [aut, cre], Hung Nguyen [aut], Tin Nguyen [fnd]

Maintainer: Duc Tran <duct at nevada.unr.edu>

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


To install this package, start R (version "4.3") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

SCFA package manual HTML R Script
Reference Manual PDF


biocViews Classification, Clustering, Software, Survival
Version 1.12.0
In Bioconductor since BioC 3.12 (R-4.0) (3.5 years)
License LGPL
Depends R (>= 4.0)
Imports matrixStats, BiocParallel, torch (>= 0.3.0), coro, igraph, Matrix, cluster, psych, glmnet, RhpcBLASctl, stats, utils, methods, survival
System Requirements
URL https://github.com/duct317/SCFA
Bug Reports https://github.com/duct317/SCFA/issues
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Suggests knitr, rmarkdown, BiocStyle
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package SCFA_1.12.0.tar.gz
Windows Binary SCFA_1.12.0.zip
macOS Binary (x86_64) SCFA_1.12.0.tgz
macOS Binary (arm64) SCFA_1.12.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/SCFA
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/SCFA
Bioc Package Browser https://code.bioconductor.org/browse/SCFA/
Package Short Url https://bioconductor.org/packages/SCFA/
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