title: The statistical analysis of spatially clustered genes under the maximum gap criterion.
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.
authors.affiliation: Computer Science Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA. roseh@cs.cmu.edu
authors.forename: Rose
authors.initials: R
authors.lastname: Hoberman
authors.forename: David
authors.initials: D
authors.lastname: Sankoff
authors.forename: Dannie
authors.initials: D
authors.lastname: Durand
mesh_terms: D001412:Bacillus subtilis / Q000235:genetics; D002874:Chromosome Mapping; D016000:Cluster Analysis; D019295:Computational Biology; D003627:Data Interpretation, Statistical; D004926:Escherichia coli / Q000235:genetics; D019143:Evolution, Molecular; D005796:Genes; D016678:Genome; D023281:Genomics; D008957:Models, Genetic; D005810:Multigene Family; D011336:Probability; D016415:Sequence Alignment; D017422:Sequence Analysis, DNA