PAM: Prediction Analysis for Microarrays

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.

• Yahoo newsgroup

• Two versions:

               Excel Add-in: Registration page; Installation guide; Manual;
             PAM for the R package   Superpc for the R package