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. 2014 Nov 15;30(22):3215-22.
doi: 10.1093/bioinformatics/btu508. Epub 2014 Jul 30.

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

Affiliations

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

Damian Smedley et al. Bioinformatics. .

Abstract

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.

Availability and implementation: http://compbio.charite.de/ExomeWalker

Contact: : peter.robinson@charite.de.

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Figures

Fig. 1.
Fig. 1.
Performance of ExomeWalker using STRING v9.05 as the source of interactome data. The bars show the percentage of exomes where the true disease gene is identified as the top hit or in the top 10 or 50 results. Either in-house or 1000 Genomes Project exomes were used. All exomes are filtered to remove synonymous, intergenic and intronic variants except for those in splice sites. In addition, variants with a MAF > 1% are excluded. Results are shown without (All) or with an AD or AR inheritance model applied. Ranking is either by Variant scoring that combines MAF and predicted pathogenicity, RWR analysis alone or ExomeWalker scoring that additionally includes evidence of protein–protein associations with other genes linked to the disease
Fig. 2.
Fig. 2.
Performance of ExomeWalker using STRING v9.05 without text-mined associations as the source of interactome data. Abbreviations are as in Figure 1
Fig. 3.
Fig. 3.
PPA network derived from congenital disorders of glycosylation, type I (CDG-I) seed genes. The candidate genes DDOST and DMP2 (shown in blue) interact with multiple other CDG-I genes (shown as red nodes in the network) via paths of length one and two. The random walk methodology essentially integrates over all interaction paths between seed genes and a candidate gene to generate a similarity score. Although short paths such as those shown in the figure have the most influence on the score, other aspects of the global network structure are also taken into account (Köhler et al., 2008)

References

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