Package: PCAPAM50 1.0.3

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:Praveen-Kumar Raj-Kumar [aut, cre, cph], Boyi Chen [aut], Ming-Wen Hu [aut], Tyler Hohenstein [aut], Jianfang Liu [aut], Craig D. Shriver [aut], Xiaoying Lin [aut, cph], Hai Hu [aut, cph]

PCAPAM50_1.0.3.tar.gz
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PCAPAM50_1.0.3.tgz(r-4.5-any)PCAPAM50_1.0.3.tgz(r-4.4-any)PCAPAM50_1.0.2.tgz(r-4.3-any)
PCAPAM50_1.0.3.tar.gz(r-4.5-noble)PCAPAM50_1.0.3.tar.gz(r-4.4-noble)
PCAPAM50_1.0.3.tgz(r-4.4-emscripten)PCAPAM50_1.0.3.tgz(r-4.3-emscripten)
PCAPAM50.pdf |PCAPAM50.html✨
PCAPAM50/json (API)
NEWS

# Install 'PCAPAM50' in R:
install.packages('PCAPAM50', repos = c('https://rajkumpismb.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.48 score 3 scripts 288 downloads 4 exports 25 dependencies

Last updated 1 months agofrom:746dc282ee. Checks:6 OK, 2 FAILURE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 08 2025
R-4.5-winOKFeb 08 2025
R-4.5-macOKFeb 08 2025
R-4.5-linuxOKFeb 08 2025
R-4.4-winOKFeb 08 2025
R-4.4-macOKFeb 08 2025
R-4.3-winOUTDATEDDec 25 2024
R-4.3-macOUTDATEDDec 25 2024

Exports:makeCalls.ihcmakeCalls.PC1ihcmakeCalls.v1PAMmy.plotPCA

Dependencies:BiobaseBiocGenericscirclizeclueclustercodetoolscolorspaceComplexHeatmapcrayondigestdoParallelforeachgenericsGetoptLongGlobalOptionsimputeIRangesiteratorslatticematrixStatspngRColorBrewerrjsonS4Vectorsshape

PCAPAM50: An R Package for Principal Component Analysis-Based Iterative PAM50 Subtyping

Praveen-Kumar Raj-Kumar Chan Soon-Shiong Institute of Molecular Medicine at Windber, Windber, PA, USA [email protected]

Rendered fromPCAPAM50_vignette.Rmdusingknitr::rmarkdownon Feb 08 2025.

Last update: 2025-01-09
Started: 2024-07-09