Fast identification and statistical evaluation of segmental homologies in comparative maps.
BACKGROUND
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.
Calabrese
Peter P
PP
Department of Mathematics, University of Southern California, Los Angeles, CA 90089, USA.
Chakravarty
Sugata
S
Vision
Todd J
TJ
D000465:Algorithms; D017360:Arabidopsis / Q000235:genetics; D001483:Base Sequence; D002874:Chromosome Mapping / Q000379:methods*; D019143:Evolution, Molecular; D020869:Gene Expression Profiling / Q000379:methods*; D014644:Genetic Variation; D016678:Genome; D008957:Models, Genetic; D015233:Models, Statistical; D008969:Molecular Sequence Data; D016415:Sequence Alignment / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods*; D012689:Sequence Homology, Nucleic Acid