| PAM: Prediction Analysis for Microarrays Class Prediction and Survival Analysis for Genomic Expression Data Mining | Features: - Performs sample classification from gene expression data, via "nearest shrunken centroid method'' of Tibshirani, Hastie, Narasimhan and Chu (2002): " Diagnosis of multiple cancer types by shrunken centroids of gene expression " (PNAS website). PNAS 2002 99:6567-6572 (May 14).
- For survival outcomes, implements 'supervised principal components' method. See
Semi-supervised methods for predicting patient survival from gene expression papers (Bair and Tibshirani) PLOS Biology, and Prediction by supervised principal components (Bair, Hastie, Paul, Tibshirani) Stanford tech report - Version 2.1 (Sep 14, 2005) featuring False discovery rates FDRs
- Version 2.0 (Mar 7, 2005) featuring: FDRs and survival analysis via supervised principal components,
- Estimates prediction error via cross-validation
- Provides a list of significant genes whose expression characterizes each diagnostic class
- Works with data from both cDNA and oligo microarrays. Can also be applied to protein expression data and SNP chip data.
- What is nearest shrunken centroids? How does it compare to other classifiers?
- Developed at Stanford University Labs. Free for all users.
Excel Add-in: Registration page; Installation guide; Manual; PAM for the R package Superpc for the R package |