pamClass: Classify using Prediction Analysis for MicroArrays
In a4Classif: Automated Affymetrix Array Analysis Classification Package

Description Usage Arguments Value Author(s) References See Also Examples

View source: R/pam.R

Classify using the Prediction Analysis for MicroArrays (PAM) algorithm as implemented in the pamr package

1	pamClass(object, groups, probe2gene = TRUE)

`object`	object containing the expression measurements; currently the only method supported is one for ExpressionSet objects
`groups`	character string indicating the column containing the class membership
`probe2gene`	logical; if `TRUE` Affymetrix probeset IDs are translated into gene symbols; if `FALSE` no such translation is conducted

object of class pamClass

Willem Talloen

Robert Tibshirani, Trevor Hastie, Balasubramanian Narasimhan, and Gilbert Chu (1999). Diagnosis of multiple cancer types by shrunken centroids of gene expression. PNAS 99: 6567-6572. Available at www.pnas.org

Goehlmann, H. and W. Talloen (2009). Gene Expression Studies Using Affymetrix Microarrays, Chapman \& Hall/CRC, p. 221.

pamr.train

if(require(ALL)){
 data(ALL, package = "ALL")
 ALL <- addGeneInfo(ALL)
 ALL$BTtype <- as.factor(substr(ALL$BT,0,1))
 resultPam <- pamClass(object = ALL, groups = "BTtype")
 plot(resultPam)
 topTable(resultPam, n = 5)
 confusionMatrix(resultPam)
}