Walking the interactome for candidate prioritization in exome sequencing studies of Mendelian diseases.
Walking the interactome for candidate prioritization in exome sequencing studies of Mendelian diseases.
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在孟德尔疾病的外显子组测序研究中，遍历相互作用组以确定候选者的优先顺序。
DOI：
10.1093/bioinformatics/btu508
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发表时间：
2014-11-15
期刊：
影响因子：
--
通讯作者：
Robinson PN
中科院分区：
文献类型：
--
作者：
Smedley D;Köhler S;Czeschik JC;Amberger J;Bocchini C;Hamosh A;Veldboer J;Zemojtel T;Robinson PN
动机：全外显子组测序(WES)开启了以前闻所未闻的在孟德尔疾病中识别新疾病基因的可能性，到目前为止，只有大约一半的基因被阐明。然而，对WES数据的解释仍然具有挑战性。结果：在这里，我们分析蛋白质-蛋白质关联(PPA)网络来确定先前与疾病有关的基因附近的候选基因。该分析采用随机游走与重启(RWR)方法，通过根据变异体的稀有性、位置和预测的致病性以及对含有变异体的基因的RWR评估来开发一个复合的变异体-基因相关性分数来适应WES的设置。使用88个疾病基因家族的已知疾病变异进行基准测试显示，正确的基因在50%的病例中排在前10名候选基因之列，我们使用2012年确定的疾病基因的前瞻性研究和该日期之前产生的≥数据证实了这一数字。我们在免费可用的Web服务器ExomeWalker中实现了我们的方法，该服务器显示了候选人的排名列表以及有关PPA、频率和预测的变异体致病性的信息，以允许快速有效地搜索可能会奖励更仔细调查的候选人。供应和实施：http://compbio.charite.de/ExomeWalker联系人：peter.robinson@charite.de
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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影响因子：
30.8
作者：
Falk, Marni J.;Zhang, Qi;Nakamaru-Ogiso, Eiko;Kannabiran, Chitra;Fonseca-Kelly, Zoe;Chakarova, Christina;Audo, Isabelle;Mackay, Donna S.;Zeitz, Christina;Borman, Arundhati Dev;Staniszewska, Magdalena;Shukla, Rachna;Palavalli, Lakshmi;Mohand-Said, Saddek;Waseem, Naushin H.;Jalali, Subhadra;Perin, Juan C.;Place, Emily;Ostrovsky, Julian;Xiao, Rui;Bhattacharya, Shomi S.;Consugar, Mark;Webster, Andrew R.;Sahel, Jose-Alain;Moore, Anthony T.;Berson, Eliot L.;Liu, Qin;Gai, Xiaowu;Pierce, Eric A.
通讯作者：
Pierce, Eric A.
来自1,092个人基因组的遗传变异的综合图。
影响因子：
64.8
作者：
通讯作者：
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影响因子：
14.9
作者：
NCBI Resource Coordinators
通讯作者：
NCBI Resource Coordinators
影响因子：
3.9
作者：
Amberger, Joanna;Bocchini, Carol;Hamosh, Ada
通讯作者：
Hamosh, Ada
影响因子：
158.5
作者：
Bochukova, Elena;Schoenmakers, Nadia;Chatterjee, Krishna
通讯作者：
Chatterjee, Krishna