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

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

Research output: Contribution to journalArticlepeer-review

45 Scopus citations


Motivation: 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.

Results: Here, 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. 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.

Original languageEnglish (US)
Pages (from-to)3215-3222
Number of pages8
Issue number22
StatePublished - Feb 27 2014

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics


Dive into the research topics of 'Walking the interactome for candidate prioritization in exome sequencing studies of Mendelian diseases'. Together they form a unique fingerprint.

Cite this