SAM

SAM(Significance Analysis of Microarrays) is a statistical technique for finding significant genes in a set of microarray experiments. It was proposed by Tusher, Tibshirani and Chu. The software was written by Balasubramanian Narasimhan.

The input to SAM is gene expression measurements from a set of microarray experiments, as well as response variable from each experiment. The response variable may be a grouping like untreated, treated [either unpaired or paired], a multiclass grouping (like breast cancer, lymphoma, colon cancer, ...), a quantitative variable ( like blood pressure) or a possibly censored survival time. SAM computes a statistic di for each gene i, measuring the strength of the relationship between gene expression and the response variable. It uses repeated permutations of the data to determine if the expression of any genes are significantly related to the response. The cutoff for significance is determined by a tuning parameter delta, chosen by the user based on the false positive rate. One can also choose a fold change parameter, to ensure that called genes change at least a prespecified amount.