PCA-PAM50 is used to perform intrinsic subtyping for breast cancer gene expression data. PCA-PAM50 leverages principal component analysis (PCA) and iterative PAM50 calls to derive the gene expression-based ER status. This generates an ER-balanced subset which is automatically used for gene centering and subsequent intrinsic calls. Thus, PCA-PAM50 performs intrinsic subtyping in ER status unbalanced cohorts.
Input is just the normalized PAM50 gene expression matrix.
The package contains two R scripts:
PCA-PAM50.R → makes use of two functions to make median values and subsequent PAM50 calls. functions_PCA-PAM50.R → provides necessary functions.
The package comes with a sample/TEST PAM50 matrix to demonstrate running the program:
‘TEST.ihc’ and ‘TEST.matrix’ is provided, substitute these to make calls for your data.
To make conventional intrinsic calls that are only using IHC, use the function “makeCalls.ihc”.
Refer to ‘PCA-PAM50.R’ to learn more, or click here.
PCA-PAM50 is an R script and should run on any computer (Linux/Unix, Windows or Mac) with R installed. However it has only been tested on Linux/Ubuntu.
Required libraries:
gplots RColorBrewer lattice genefilter ctc heatmap.plus
Libraries can be installed through R Bioconductor like this:
source("https://bioconductor.org/biocLite.R") BiocLite(library)
Copyright 2018 Windber Reseach Institute, Windber, PA – 15963. All Rights Reserved.
Contact:
Developer: Praveen K. Raj Kumar [P.RajKumar@wriwindber.org]
Lab director: Hai Hu [H.hu@wriwindber.org]
This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
You should have received a copy of the GNU General Public License along with this program. If not, see GNU licenses.