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
| Maintainer | Duc Tran <duct@nevada.unr.edu> |
| Author | Duc Tran [aut, cre], Hung Nguyen [aut], Tin Nguyen [fnd] |
| License | LGPL |
| URL | https://github.com/duct317/SCFA |
| Bug Reports | https://github.com/duct317/SCFA/issues |
| Downloads rank | 237 |
| Source branch | RELEASE_3_23 |
| biocViews | Classification, Clustering, Software, Survival |
Documentation
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Dependencies
Depends: R (>= 4.0)
Imports: matrixStats, BiocParallel, torch (>= 0.3.0), coro, igraph, Matrix, cluster, psych, glmnet, RhpcBLASctl, stats, utils, methods, survival