Identification of deleterious synonymous variants in human genomes

The prioritization and identification of disease-causing mutations is one of the most significant challenges in medical genomics. Currently available methods address this problem for non-synonymous single nucleotide variants (SNVs) and variation in promoters/enhancers; however, recent research has i...

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Veröffentlicht in:Bioinformatics 2013-08, Vol.29 (15), p.1843-1850
Hauptverfasser: Buske, Orion J, Manickaraj, AshokKumar, Mital, Seema, Ray, Peter N, Brudno, Michael
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container_end_page 1850
container_issue 15
container_start_page 1843
container_title Bioinformatics
container_volume 29
creator Buske, Orion J
Manickaraj, AshokKumar
Mital, Seema
Ray, Peter N
Brudno, Michael
description The prioritization and identification of disease-causing mutations is one of the most significant challenges in medical genomics. Currently available methods address this problem for non-synonymous single nucleotide variants (SNVs) and variation in promoters/enhancers; however, recent research has implicated synonymous (silent) exonic mutations in a number of disorders. We have curated 33 such variants from literature and developed the Silent Variant Analyzer (SilVA), a machine-learning approach to separate these from among a large set of rare polymorphisms. We evaluate SilVA's performance on in silico 'infection' experiments, in which we implant known disease-causing mutations into a human genome, and show that for 15 of 33 disorders, we rank the implanted mutation among the top five most deleterious ones. Furthermore, we apply the SilVA method to two additional datasets: synonymous variants associated with Meckel syndrome, and a collection of silent variants clinically observed and stratified by a molecular diagnostics laboratory, and show that SilVA is able to accurately predict the harmfulness of silent variants in these datasets. SilVA is open source and is freely available from the project website: http://compbio.cs.toronto.edu/silva silva-snv@cs.toronto.edu Supplementary data are available at Bioinformatics online.
doi_str_mv 10.1093/bioinformatics/btt308
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subjects Artificial Intelligence
Ciliary Motility Disorders - genetics
Computer Simulation
Disease - genetics
Encephalocele - genetics
Exons
Genome, Human
Genomics - methods
Humans
Mutation
Polycystic Kidney Diseases - genetics
Polymorphism, Genetic
title Identification of deleterious synonymous variants in human genomes
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