Package: PCAPAM50 1.0.2
Praveen-Kumar Raj-Kumar
PCAPAM50: Enhanced 'PAM50' Subtyping of Breast Cancer
Accurate classification of breast cancer tumors based on gene expression data is not a trivial task, and it lacks standard practices.The 'PAM50' classifier, which uses 50 gene centroid correlation distances to classify tumors, faces challenges with balancing estrogen receptor (ER) status and gene centering. The 'PCAPAM50' package leverages principal component analysis and iterative 'PAM50' calls to create a gene expression-based ER-balanced subset for gene centering, avoiding the use of protein expression-based ER data resulting into an enhanced Breast Cancer subtyping.
Authors:
PCAPAM50_1.0.2.tar.gz
PCAPAM50_1.0.2.tar.gz(r-4.5-noble)PCAPAM50_1.0.2.tar.gz(r-4.4-noble)
PCAPAM50_1.0.2.tgz(r-4.4-emscripten)PCAPAM50_1.0.2.tgz(r-4.3-emscripten)
PCAPAM50.pdf |PCAPAM50.html✨
PCAPAM50/json (API)
NEWS
| # Install 'PCAPAM50' in R: |
| install.packages('PCAPAM50', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 days agofrom:64cee3ecbf. Checks:OK: 2. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 25 2024 |
| R-4.5-linux | OK | Nov 25 2024 |
Exports:makeCalls.ihcmakeCalls.PC1ihcmakeCalls.v1PAMmy.plotPCA
Dependencies:BiobaseBiocGenericscirclizeclueclustercodetoolscolorspaceComplexHeatmapcrayondigestdoParallelforeachgenericsGetoptLongGlobalOptionsimputeIRangesiteratorslatticematrixStatspngRColorBrewerrjsonS4Vectorsshape
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Make a Conventional PAM50 Intrinsic Subtype Calls | makeCalls.ihc |
| Make intermediate intrinsic subtype calls | makeCalls.PC1ihc |
| Make PCAPAM50 calls | makeCalls.v1PAM |
| Modeling after plotPCA of DESeq | my.plotPCA |
