Abstract

Abstract Motivation: Chromosomal segments that share common ancestry, either through genomic duplication or species divergence, are said to be segmental homologs of one another. Their identification allows researchers to leverage knowledge of model organisms for use in other systems and is of value for studies of genome evolution. However, identification and statistical evaluation of segmental homologies can be a challenge when the segments are highly diverged. Results: We describe a flexible dynamic programming algorithm for the identification of segments having multiple homologous features. We model the probability of observing putative segmental homologies by chance and incorporate our findings into the parameterization of the algorithm and the statistical evaluation of its output. Combined, these findings allow segmental homologies to be identified in comparisons within and between genomic maps in a rigorous, rapid, and automated fashion. Availability: http://www.bio.unc.edu/faculty/vision/lab/ Contact: tjv@bio.unc.edu Keywords: homology, comparative maps, synteny, genome evolution *To whom correspondence should be addressed.

Keywords

SyntenyIdentification (biology)Leverage (statistics)Segmental duplicationGenomeHomology (biology)Computational biologyBiologyDivergence (linguistics)Computer scienceArtificial intelligenceEvolutionary biologyGeneticsGene

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Publication Info

Year
2003
Type
article
Volume
19
Issue
suppl_1
Pages
i74-i80
Citations
93
Access
Closed

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Peter Calabrese, Sugata Chakravarty, Todd Vision (2003). Fast identification and statistical evaluation ofsegmental homologies in comparative maps. Bioinformatics , 19 (suppl_1) , i74-i80. https://doi.org/10.1093/bioinformatics/btg1008

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DOI
10.1093/bioinformatics/btg1008