Abstract
Young et al., (2010) showed that due to gene length bias the popular Fisher Exact Test should not be used to study the association between a group of differentially expressed (DE) genes and a specific Gene Ontology (GO) category. Instead they suggest a test where one conditions on the genes in the GO category and draws the pseudo DE expressed genes according to a length-dependent distribution. The same model was presented in a different context by Kazemian et al., (2011) who went on to offer a dynamic programming (DP) algorithm to exactly compute the significance of the proposed test. Here we point out that while valid, the test proposed by these authors is no longer symmetric as Fisher's Exact Test is: one gets different answers if one conditions on the observed GO category than on the DE set. As an alternative we offer a symmetric generalization of Fisher's Exact Test and provide efficient algorithms to evaluate its significance.
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