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The statistical analysis of spatially clustered genes under the maximum gap criterion
Rose Hoberman1, David Sankoff, Dannie Durand
1Computer Science Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA. roseh@cs.cmu.edu
Abstract:
Statistical validation of gene clusters is imperative for many important applications in comparative genomics which depend on the identification of genomic regions that are historically and/or functionally related. We develop the first rigorous statistical treatment of max-gap clusters, a cluster definition frequently used in empirical studies. We present exact expressions for the probability of observing an individual cluster of a set of marked genes in one genome, as well as upper and lower bounds on the probability of observing a cluster of h homologs in a pairwise whole-genome comparison. We demonstrate the utility of our approach by applying it to a whole-genome comparison of E. coli and B. subtilis. Code for statistical tests is available at.
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