Package: SCFA
Type: Package
Title: SCFA: Subtyping via Consensus Factor Analysis
Version: 1.6.0
Authors@R: c(
    person("Duc", "Tran", , "duct@nevada.unr.edu", role = c("aut", "cre")),
    person("Hung", "Nguyen", role = c("aut")),
    person("Tin", "Nguyen", role = c("fnd"))
    )
Description: 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.
License: LGPL
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0)
Imports: matrixStats, keras, tensorflow, BiocParallel, igraph, Matrix,
        cluster, clusterCrit, psych, glmnet, RhpcBLASctl, stats, utils,
        methods, survival
RoxygenNote: 7.1.1
biocViews: Survival, Clustering, Classification
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/duct317/SCFA
BugReports: https://github.com/duct317/SCFA/issues
git_url: https://git.bioconductor.org/packages/SCFA
git_branch: RELEASE_3_15
git_last_commit: daa94d2
git_last_commit_date: 2022-04-26
Date/Publication: 2022-04-26
NeedsCompilation: no
Packaged: 2022-04-27 01:04:00 UTC; biocbuild
Author: Duc Tran [aut, cre],
  Hung Nguyen [aut],
  Tin Nguyen [fnd]
Maintainer: Duc Tran <duct@nevada.unr.edu>
Built: R 4.2.0; ; 2022-04-27 10:04:31 UTC; windows
