Assessing the pathogenicity of insertion and deletion variants with the Variant Effect Scoring Tool (VEST-Indel)

Douville, Christopher, Masica, David L., Stenson, Peter Daniel, Cooper, David Neil ORCID: https://orcid.org/0000-0002-8943-8484, Gygax, Derek M., Kim, Rick, Ryan, Michael and Karchin, Rachel 2015. Assessing the pathogenicity of insertion and deletion variants with the Variant Effect Scoring Tool (VEST-Indel). Human Mutation 37 (1) , pp. 28-35. 10.1002/humu.22911

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Abstract

Insertion/deletion variants (indels) alter protein sequence and length, yet are highly prevalent in healthy populations, presenting a challenge to bioinformatics classifiers. Commonly used features—DNA and protein sequence conservation, indel length, and occurrence in repeat regions—are useful for inference of protein damage. However, these features can cause false positives when predicting the impact of indels on disease. Existing methods for indel classification suffer from low specificities, severely limiting clinical utility. Here, we further develop our variant effect scoring tool (VEST) to include the classification of in-frame and frameshift indels (VEST-indel) as pathogenic or benign. We apply 24 features, including a new “PubMed” feature, to estimate a gene's importance in human disease. When compared with four existing indel classifiers, our method achieves a drastically reduced false-positive rate, improving specificity by as much as 90%. This approach of estimating gene importance might be generally applicable to missense and other bioinformatics pathogenicity predictors, which often fail to achieve high specificity. Finally, we tested all possible meta-predictors that can be obtained from combining the four different indel classifiers using Boolean conjunctions and disjunctions, and derived a meta-predictor with improved performance over any individual method.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Medicine
Additional Information:	This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
Publisher:	Wiley-Blackwell
ISSN:	1059-7794
Date of First Compliant Deposit:	30 March 2016
Date of Acceptance:	14 September 2015
Last Modified:	05 May 2023 23:25
URI:	https://orca.cardiff.ac.uk/id/eprint/84271

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