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

被引:82
作者
Frousios, Kimon [1 ]
Iliopoulos, Costas S. [1 ]
Schlitt, Thomas [2 ,3 ]
Simpson, Michael A. [3 ]
机构
[1] Kings Coll London, Dept Informat, London WC2R 2LS, England
[2] Kings Coll London, Inst Math & Mol Biomed, London SE1 1UL, England
[3] Kings Coll London, Sch Med, Dept Med & Mol Genet, Guys Hosp, London SE1 9RT, England
关键词
Coding; DNA; Variant; Function; Prediction; SNP; SNP; MUTATIONS; DATABASE; DISEASE; ANNOTATION; SCORE; POLYMORPHISMS; GENE;
D O I
10.1016/j.ygeno.2013.06.005
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
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. (C) 2013 The Authors. Published by Elsevier Inc. All rights reserved.
引用
收藏
页码:223 / 228
页数:6
相关论文
共 39 条
[1]   A method and server for predicting damaging missense mutations [J].
Adzhubei, Ivan A. ;
Schmidt, Steffen ;
Peshkin, Leonid ;
Ramensky, Vasily E. ;
Gerasimova, Anna ;
Bork, Peer ;
Kondrashov, Alexey S. ;
Sunyaev, Shamil R. .
NATURE METHODS, 2010, 7 (04) :248-249
[2]   A map of human genome variation from population-scale sequencing [J].
Altshuler, David ;
Durbin, Richard M. ;
Abecasis, Goncalo R. ;
Bentley, David R. ;
Chakravarti, Aravinda ;
Clark, Andrew G. ;
Collins, Francis S. ;
De la Vega, Francisco M. ;
Donnelly, Peter ;
Egholm, Michael ;
Flicek, Paul ;
Gabriel, Stacey B. ;
Gibbs, Richard A. ;
Knoppers, Bartha M. ;
Lander, Eric S. ;
Lehrach, Hans ;
Mardis, Elaine R. ;
McVean, Gil A. ;
Nickerson, DebbieA. ;
Peltonen, Leena ;
Schafer, Alan J. ;
Sherry, Stephen T. ;
Wang, Jun ;
Wilson, Richard K. ;
Gibbs, Richard A. ;
Deiros, David ;
Metzker, Mike ;
Muzny, Donna ;
Reid, Jeff ;
Wheeler, David ;
Wang, Jun ;
Li, Jingxiang ;
Jian, Min ;
Li, Guoqing ;
Li, Ruiqiang ;
Liang, Huiqing ;
Tian, Geng ;
Wang, Bo ;
Wang, Jian ;
Wang, Wei ;
Yang, Huanming ;
Zhang, Xiuqing ;
Zheng, Huisong ;
Lander, Eric S. ;
Altshuler, David L. ;
Ambrogio, Lauren ;
Bloom, Toby ;
Cibulskis, Kristian ;
Fennell, Tim J. ;
Gabriel, Stacey B. .
NATURE, 2010, 467 (7319) :1061-1073
[3]  
[Anonymous], 1999, Advances in kernel methods: Support vector learning
[4]   Ongoing and future developments at the Universal Protein Resource [J].
Apweiler, Rolf ;
Martin, Maria Jesus ;
O'Donovan, Claire ;
Magrane, Michele ;
Alam-Faruque, Yasmin ;
Antunes, Ricardo ;
Barrell, Daniel ;
Bely, Benoit ;
Bingley, Mark ;
Binns, David ;
Bower, Lawrence ;
Browne, Paul ;
Chan, Wei Mun ;
Dimmer, Emily ;
Eberhardt, Ruth ;
Fazzini, Francesco ;
Fedotov, Alexander ;
Foulger, Rebecca ;
Garavelli, John ;
Castro, Leyla Garcia ;
Huntley, Rachael ;
Jacobsen, Julius ;
Kleen, Michael ;
Laiho, Kati ;
Legge, Duncan ;
Lin, Quan ;
Liu, Wudong ;
Luo, Jie ;
Orchard, Sandra ;
Patient, Samuel ;
Pichler, Klemens ;
Poggioli, Diego ;
Pontikos, Nikolas ;
Pruess, Manuela ;
Rosanoff, Steven ;
Sawford, Tony ;
Sehra, Harminder ;
Turner, Edward ;
Corbett, Matt ;
Donnelly, Mike ;
van Rensburg, Pieter ;
Xenarios, Ioannis ;
Bougueleret, Lydie ;
Auchincloss, Andrea ;
Argoud-Puy, Ghislaine ;
Axelsen, Kristian ;
Bairoch, Amos ;
Baratin, Delphine ;
Blatter, Marie-Claude ;
Boeckmann, Brigitte .
NUCLEIC ACIDS RESEARCH, 2011, 39 :D214-D219
[5]   Assessing the accuracy of prediction algorithms for classification: an overview [J].
Baldi, P ;
Brunak, S ;
Chauvin, Y ;
Andersen, CAF ;
Nielsen, H .
BIOINFORMATICS, 2000, 16 (05) :412-424
[6]   nsSNPAnalyzer: identifying disease-associated nonsynonymous single nucleotide polymorphisms [J].
Bao, L ;
Zhou, M ;
Cui, Y .
NUCLEIC ACIDS RESEARCH, 2005, 33 :W480-W482
[7]   Statistical geometry based prediction of nonsynonymous SNP functional effects using random forest and neuro-fuzzy classifiers [J].
Barenboim, Maxim ;
Masso, Majid ;
Vaisman, Iosif I. ;
Jamison, D. Curtis .
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, 2008, 71 (04) :1930-1939
[8]   SNAP: predict effect of non-synonymous polymorphisms on function [J].
Bromberg, Yana ;
Rost, Burkhard .
NUCLEIC ACIDS RESEARCH, 2007, 35 (11) :3823-3835
[9]   Functional Annotations Improve the Predictive Score of Human Disease-Related Mutations in Proteins [J].
Calabrese, Remo ;
Capriotti, Emidio ;
Fariselli, Piero ;
Martelli, Pier Luigi ;
Casadio, Rita .
HUMAN MUTATION, 2009, 30 (08) :1237-1244
[10]   Predicting the insurgence of human genetic diseases associated to single point protein mutations with support vector machines and evolutionary information [J].
Capriotti, E. ;
Calabrese, R. ;
Casadio, R. .
BIOINFORMATICS, 2006, 22 (22) :2729-2734