Walking the interactome for candidate prioritization in exome sequencing studies of Mendelian diseases

Smedley, Damian; Kohler, Sebastian; Czeschik, Johanna Christina; Amberger, Joanna; Bocchini, Carol; Hamosh, Ada; Veldboer, Julian; Zemojtel, Tomasz; Robinson, Peter N.

doi:10.1093/bioinformatics/btu508

Title: Walking the interactome for candidate prioritization in exome sequencing studies of Mendelian diseases

Journal Article · Wed Jul 30 00:00:00 EDT 2014 · Bioinformatics

DOI:https://doi.org/10.1093/bioinformatics/btu508· OSTI ID:1342955

Smedley, Damian ^[1]; Kohler, Sebastian ^[2]; Czeschik, Johanna Christina ^[3]; Amberger, Joanna ^[4]; Bocchini, Carol ^[4]; Hamosh, Ada ^[4]; Veldboer, Julian ^[5]; Zemojtel, Tomasz ^[6]; Robinson, Peter N. ^[7]

The Wellcome Trust Sanger Institute, Cambridgeshire (United Kingdom)
Charite-Univ. Berlin, Berlin (Germany)
Univ. of Duisburg-Essen, Essen (Germany)
Johns Hopkins Univ. School of Medicine, Baltimore, MD (United States)
Charite-Univ. Berlin, Berlin (Germany); Freie Univ. Berlin, Berlin (Germany)
Charite-Univ. Berlin, Berlin (Germany); Polish Academy of Sciences, Poznan (Poland)
Charite-Univ. Berlin, Berlin (Germany); Freie Univ. Berlin, Berlin (Germany); Max Planck Institute for Molecular Genetics, Berlin (Germany)

Here, whole-exome sequencing (WES) has opened up previously unheard of possibilities for identifying novel disease genes in Mendelian disorders, only about half of which have been elucidated to date. However, interpretation of WES data remains challenging. As a result, we analyze protein–protein association (PPA) networks to identify candidate genes in the vicinity of genes previously implicated in a disease. The analysis, using a random-walk with restart (RWR) method, is adapted to the setting of WES by developing a composite variant-gene relevance score based on the rarity, location and predicted pathogenicity of variants and the RWR evaluation of genes harboring the variants. Benchmarking using known disease variants from 88 disease-gene families reveals that the correct gene is ranked among the top 10 candidates in ≥50% of cases, a figure which we confirmed using a prospective study of disease genes identified in 2012 and PPA data produced before that date. In conclusion, we implement our method in a freely available Web server, ExomeWalker, that displays a ranked list of candidates together with information on PPAs, frequency and predicted pathogenicity of the variants to allow quick and effective searches for candidates that are likely to reward closer investigation.

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Research Organization:: Johns Hopkins Univ., Baltimore, MD (United States). School of Medicine

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES)

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 1342955

Journal Information:: Bioinformatics, Vol. 30, Issue 22; ISSN 1367-4803

Publisher:: Oxford University PressCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 55 works

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