Elsevier

Genomics

Volume 102, Issue 4, October 2013, Pages 223-228
Genomics

Predicting the functional consequences of non-synonymous DNA sequence variants — evaluation of bioinformatics tools and development of a consensus strategy

https://doi.org/10.1016/j.ygeno.2013.06.005Get rights and content
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Highlights

  • We benchmark 8 SNP effect prediction tools and use them in a consensus strategy.

  • Dataset of disease-causing SNPs from HGMD and common SNPs from 1000 Genomes Project

  • PolyPhen2 found to be most sensitive method, SNPs&GO most selective.

  • Consensus outperforms previous similar efforts and individual tools.

  • Consensus tool (CoVEC) available via the web or local scripts

Abstract

The study of DNA sequence variation has been transformed by recent advances in DNA sequencing technologies. Determination of the functional consequences of sequence variant alleles offers potential insight as to how genotype may influence phenotype. Even within protein coding regions of the genome, establishing the consequences of variation on gene and protein function is challenging and requires substantial laboratory investigation. However, a series of bioinformatics tools have been developed to predict whether non-synonymous variants are neutral or disease-causing. In this study we evaluate the performance of nine such methods (SIFT, PolyPhen2, SNPs&GO, PhD-SNP, PANTHER, Mutation Assessor, MutPred, Condel and CAROL) and developed CoVEC (Consensus Variant Effect Classification), a tool that integrates the prediction results from four of these methods. We demonstrate that the CoVEC approach outperforms most individual methods and highlights the benefit of combining results from multiple tools.

Keywords

Coding
DNA
Variant
Function
Prediction
SNP

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