SAM or Significance Analysis of Microarray is a robust method initially designed for identification of statistically significant genes in data from gene expression microarray. In particular, it provides researchers with a non-parametric score for each gene based on repeated measurements.
SAM use moderated t-tests to computes a statistic dj for each gene j, which measures the strength of the relationship between gene expression (X) and a response variable (Y). This analysis uses non-parametric statistics by repeated permutations of the data to determine if the expression of any gene is significant related to the response. The procedure accounts for correlations in genes and avoids normal assumptions about the distribution of individual genes. A typical SAM output is shown below. More detailed description about about SAM history, features, and instructions can be found here.
A recent study has shown that SAM may lose certain power in general statistical tests to correctly detect significant features which violate homogeneity.