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===Significance analysis of microarrays (SAM)===
Significance analysis of microarrays (SAM) is a [[statistics|statistical technique]] for determining whether changes in [[gene expression]] are statistically significant. It was established in 2001 by Virginia Tusher, [[Robert Tibshirani]] and [[Gilbert Chu]], and is distributed in an [[R (programming language)|R-package]] by [[Stanford University]].
[[File:Significance analysis of microarry output.jpg|thumb|significance analysis of microarry (SAM) screenshot]]
SAM identifies statistically significant genes by carrying out gene specific [[Student's t-test|t-tests]] and computes a statistic ''d<sub>j</sub>'' for each gene ''j'', which measures the strength of the relationship between gene expression and a response variable.<ref name="R4"/><ref name="R5"/><ref name="R6"/> This analysis uses [[non-parametric statistics]], since the data may not follow a [[normal distribution]]. The response variable describes and groups the data based on experimental conditions. In this method, repeated [[permutations]] of the data are used to determine if the expression of any gene is significant related to the response. The use of permutation-based analysis accounts for correlations in genes and avoids [[wikt:Special:Search/parametric|parametric]] assumptions about the distribution of individual genes. This is an advantage over other techniques (e.g., [[ANOVA]] and [[Bonferroni correction]]), which assume equal variance and/or independence of genes.<ref name="R7"/>
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