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

Abstract

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.

Authors:
 [1];  [2];  [3];  [4];  [4];  [4];  [5];  [6];  [7]
  1. The Wellcome Trust Sanger Institute, Cambridgeshire (United Kingdom)
  2. Charite-Univ. Berlin, Berlin (Germany)
  3. Univ. of Duisburg-Essen, Essen (Germany)
  4. Johns Hopkins Univ. School of Medicine, Baltimore, MD (United States)
  5. Charite-Univ. Berlin, Berlin (Germany); Freie Univ. Berlin, Berlin (Germany)
  6. Charite-Univ. Berlin, Berlin (Germany); Polish Academy of Sciences, Poznan (Poland)
  7. Charite-Univ. Berlin, Berlin (Germany); Freie Univ. Berlin, Berlin (Germany); Max Planck Institute for Molecular Genetics, Berlin (Germany)
Publication Date:
Research Org.:
Johns Hopkins Univ., Baltimore, MD (United States). School of Medicine
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)
OSTI Identifier:
1342955
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Bioinformatics
Additional Journal Information:
Journal Volume: 30; Journal Issue: 22; Journal ID: ISSN 1367-4803
Publisher:
Oxford University Press
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES

Citation Formats

Smedley, Damian, Kohler, Sebastian, Czeschik, Johanna Christina, Amberger, Joanna, Bocchini, Carol, Hamosh, Ada, Veldboer, Julian, Zemojtel, Tomasz, and Robinson, Peter N. Walking the interactome for candidate prioritization in exome sequencing studies of Mendelian diseases. United States: N. p., 2014. Web. doi:10.1093/bioinformatics/btu508.
Smedley, Damian, Kohler, Sebastian, Czeschik, Johanna Christina, Amberger, Joanna, Bocchini, Carol, Hamosh, Ada, Veldboer, Julian, Zemojtel, Tomasz, & Robinson, Peter N. Walking the interactome for candidate prioritization in exome sequencing studies of Mendelian diseases. United States. doi:10.1093/bioinformatics/btu508.
Smedley, Damian, Kohler, Sebastian, Czeschik, Johanna Christina, Amberger, Joanna, Bocchini, Carol, Hamosh, Ada, Veldboer, Julian, Zemojtel, Tomasz, and Robinson, Peter N. Wed . "Walking the interactome for candidate prioritization in exome sequencing studies of Mendelian diseases". United States. doi:10.1093/bioinformatics/btu508. https://www.osti.gov/servlets/purl/1342955.
@article{osti_1342955,
title = {Walking the interactome for candidate prioritization in exome sequencing studies of Mendelian diseases},
author = {Smedley, Damian and Kohler, Sebastian and Czeschik, Johanna Christina and Amberger, Joanna and Bocchini, Carol and Hamosh, Ada and Veldboer, Julian and Zemojtel, Tomasz and Robinson, Peter N.},
abstractNote = {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.},
doi = {10.1093/bioinformatics/btu508},
journal = {Bioinformatics},
number = 22,
volume = 30,
place = {United States},
year = {Wed Jul 30 00:00:00 EDT 2014},
month = {Wed Jul 30 00:00:00 EDT 2014}
}

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Cited by: 23 works
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