An integrative approach to predicting the functional effects of small indels in non-coding regions of the human genome.
An integrative approach to predicting the functional effects of small indels in non-coding regions of the human genome.
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DOI：
10.1186/s12859-017-1862-y
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发表时间：
2017-10-06
影响因子：
3
通讯作者：
Campbell C
中科院分区：
文献类型：
--
作者：
Ferlaino M;Rogers MF;Shihab HA;Mort M;Cooper DN;Gaunt TR;Campbell C
小的插入和缺失（indels）在人类疾病中具有显著的影响，就频率而言，它们是仅次于单核苷酸变异的致病突变。由于与复杂性状相关的大多数突变位于外显子组之外，因此研究人类基因组非编码区中indel的潜在致病影响至关重要。我们提出了FATHMM-indel，一种预测人类基因组非编码区indel的功能效应（致病性或中性）的综合方法。我们的方法利用除了序列数据之外的各种基因组注释。当在基准数据上验证时，FATHMM-indel显著优于CADD和GAVIN，在评估非编码变体的致病性影响方面的最新模型。FATHMM-indel可通过网络服务器indels.biocompute.org.uk获得。FATHMM-indel可以准确预测功能影响，并优先考虑整个非编码基因组中的小indel。本文的在线版本（doi：10.1186/s12859-017-1862-y）包含补充材料，可供授权用户使用。
Small insertions and deletions (indels) have a significant influence in human disease and, in terms of frequency, they are second only to single nucleotide variants as pathogenic mutations. As the majority of mutations associated with complex traits are located outside the exome, it is crucial to investigate the potential pathogenic impact of indels in non-coding regions of the human genome. We present FATHMM-indel, an integrative approach to predict the functional effect, pathogenic or neutral, of indels in non-coding regions of the human genome. Our method exploits various genomic annotations in addition to sequence data. When validated on benchmark data, FATHMM-indel significantly outperforms CADD and GAVIN, state of the art models in assessing the pathogenic impact of non-coding variants. FATHMM-indel is available via a web server at indels.biocompute.org.uk. FATHMM-indel can accurately predict the functional impact and prioritise small indels throughout the whole non-coding genome. The online version of this article (doi:10.1186/s12859-017-1862-y) contains supplementary material, which is available to authorized users.
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影响因子：
3.9
作者：
Shihab, Hashem A.;Gough, Julian;Cooper, David N.;Stenson, Peter D.;Barker, Gary L. A.;Edwards, Keith J.;Day, Ian N. M.;Gaunt, Tom R.
通讯作者：
Gaunt, Tom R.
影响因子：
30.8
作者：
Kircher, Martin;Witten, Daniela M.;Jain, Preti;O'Roak, Brian J.;Cooper, Gregory M.;Shendure, Jay
通讯作者：
Shendure, Jay
影响因子：
12.3
作者：
van der Velde KJ;de Boer EN;van Diemen CC;Sikkema-Raddatz B;Abbott KM;Knopperts A;Franke L;Sijmons RH;de Koning TJ;Wijmenga C;Sinke RJ;Swertz MA
通讯作者：
Swertz MA
影响因子：
7
作者：
Siepel, A;Bejerano, G;Haussler, D
通讯作者：
Haussler, D
影响因子：
7
作者：
Pollard, Katherine S.;Hubisz, Melissa J.;Siepel, Adam
通讯作者：
Siepel, Adam