Package: SCFA 1.22.0

Duc Tran

SCFA: SCFA: Subtyping via Consensus Factor Analysis

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.

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

SCFA_1.22.0.tar.gz
SCFA_1.22.0.zip(r-4.7)SCFA_1.22.0.zip(r-4.6)SCFA_1.22.0.zip(r-4.5)
SCFA_1.22.0.tgz(r-4.6-any)SCFA_1.22.0.tgz(r-4.5-any)
SCFA_1.22.0.tar.gz(r-4.7-any)SCFA_1.22.0.tar.gz(r-4.6-any)
SCFA_1.22.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
SCFA/json (API)

# Install 'SCFA' in R:

install.packages('SCFA', repos = c('https://bioc-release.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/duct317/scfa/issues

Datasets:

GBM - GBM

On BioConductor:SCFA-1.23.0(bioc 3.24)SCFA-1.22.0(bioc 3.23)

survival clustering classification

4.48 score 3 stars 3 scripts 1 mentions 2 exports 51 dependencies

Last updated from:b0c16c711b (on RELEASE_3_23). Checks:1 NOTE, 9 OK. Indexed: no.

Target	Result	Time
bioc-checks	NOTE	182
linux-devel-x86_64	OK	371
source / vignettes	OK	343
linux-release-x86_64	OK	334
macos-release-arm64	OK	200
macos-oldrel-arm64	OK	200
windows-devel	OK	307
windows-release	OK	284
windows-oldrel	OK	307
wasm-release	OK	160