VERA & SAM 1.0
VERA & SAM (Variability and ERror Assessment and Significance of Array Measurement) Estimates error model parameters from replicated, preprocessed experiments, and uses error model to improve the accuracy of the expression ratio and to assign a value ‘lambda’ to each gene, indicating the likelihood that the gene is differentially expressed.
VERA and SAM are a pair of programs that provide a method to determine whether any given gene is expressed at a different level in one cell population than in another according to microarray data.
Trey Ideker ,Vesteinn Thorsson (thorsson AT SYMBOLsystemsbiology DOT org) etc.
- Linux / Windows
:: MORE INFORMATION
T. Ideker, V. Thorsson, A. F. Siegel, and L. Hood.
Testing for differentially-expressed genes by maximum-likelihood analysis of microarray data
Journal of Computational Biology 7 (6) 805-817 (2000).