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Automated splice site analysis

Posted on:2006-05-09Degree:M.SType:Thesis
University:University of Missouri - Kansas CityCandidate:Nalla, Vijay Kumar ReddyFull Text:PDF
GTID:2450390008467928Subject:Computer Science
Abstract/Summary:
Information theory-based software tools have been useful in interpreting noncoding sequence variation within functional sequence elements such as splice sites. Individual information analysis detects activated cryptic splice sites and associated splicing regulatory sites and is capable of distinguishing null from partially functional alleles. We present a server (https://splice.cmh.edu) designed to analyze splicing mutations in binding sites in either human genes, genome-mapped mRNAs, user-defined sequences, or dbSNP entries. Standard HUGO-approved gene symbols and HGVS-approved systematic mutation nomenclature (or dbSNP format) are entered via a web portal. The software was validated by analyzing ∼1,300 mutations from Human Mutation as well as eight mapped SNPs from dbSNP designated as splice site variants. All of the splicing mutations and variants affected splice site strength or activated cryptic splice sites. The server also detected several missense mutations that were unexpectedly predicted to have concomitant effects on splicing. The server also predicts the relative use of different cryptic sites based on total exon splicing information.
Keywords/Search Tags:Splice site, Splicing
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