Package: SCFA 1.23.0

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_1.23.0.tar.gz
SCFA_1.23.0.zip(r-4.7)SCFA_1.23.0.zip(r-4.6)SCFA_1.23.0.zip(r-4.5)
SCFA_1.23.0.tgz(r-4.6-any)SCFA_1.23.0.tgz(r-4.5-any)
SCFA_1.23.0.tar.gz(r-4.7-any)SCFA_1.23.0.tar.gz(r-4.6-any)
SCFA_1.23.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
SCFA/json (API)
NEWS

# Install 'SCFA' in R:

install.packages('SCFA', repos = c('https://bioc.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 304 downloads 1 mentions 2 exports 51 dependencies

Last updated from:7a31c30a54. Checks:1 NOTE, 9 OK. Indexed: yes.

Target	Result	Time
bioc-checks	NOTE	169
linux-devel-x86_64	OK	369
source / vignettes	OK	356
linux-release-x86_64	OK	367
macos-release-arm64	OK	259
macos-oldrel-arm64	OK	254
windows-devel	OK	421
windows-release	OK	334
windows-oldrel	OK	346
wasm-release	OK	137