High-throughput analysis of epistasis in genome-wide association studies with BiForce.
High-throughput analysis of epistasis in genome-wide association studies with BiForce.
复制标题
DOI：
10.1093/bioinformatics/bts304
复制
发表时间：
2012-08-01
期刊：
影响因子：
--
通讯作者：
Wei WH
中科院分区：
文献类型：
--
作者：
Gyenesei A;Moody J;Semple CA;Haley CS;Wei WH
动机：基因-基因相互作用(上位性)被认为在形成复杂特征方面很重要，但由于列举数十亿个单核苷酸多态(SNP)组合的计算挑战，它们在全基因组关联研究(Gwas)中一直被探索得不够。需要快速筛查工具才能使上位性分析在GWAS中常规可用。结果：我们提出了BiForce来支持高通量的数量或二元疾病(病例对照)性状的上位性分析。BiForce通过使用高效内存的数据结构、布尔位操作和多线程并行化实现了极高的计算效率。它执行全成对基因组扫描，使用适当的Bonferroni校正的显着性阈值来检测涉及具有或不具有显著边缘效应的SNPs的相互作用。在模拟数据集和真实数据集上的一系列性能测试中，我们表明BiForce在二进制和数量特征方面比已发表的工具更强大，速度也更快。在一个32节点的计算集群上，我们展示了BiForce在分析GWAS队列(323 697个SNPs，4500个个体)和另一个队列(340,000个SNPs，1750个病例和1500个对照)中的两个疾病特征中的八个代谢性状。BiForce在1天内完成了对8个代谢性状的分析，在5个代谢性状中鉴定出9对上位SNP，在2个疾病性状中鉴定出18对SNP。BiForce可以使上位性分析成为GWAS的常规练习，从而提高我们对上位性在复杂性状遗传调控中的作用的理解。可获得性和实施：该软件是免费的，可以从http://bioinfo.utu.fi/BiForce/.下载联系人：wenhua.wei@igmm.ed.ac.uk补充信息：生物信息学在线提供补充数据。
Motivation: Gene–gene interactions (epistasis) are thought to be important in shaping complex traits, but they have been under-explored in genome-wide association studies (GWAS) due to the computational challenge of enumerating billions of single nucleotide polymorphism (SNP) combinations. Fast screening tools are needed to make epistasis analysis routinely available in GWAS. Results: We present BiForce to support high-throughput analysis of epistasis in GWAS for either quantitative or binary disease (case–control) traits. BiForce achieves great computational efficiency by using memory efficient data structures, Boolean bitwise operations and multithreaded parallelization. It performs a full pair-wise genome scan to detect interactions involving SNPs with or without significant marginal effects using appropriate Bonferroni-corrected significance thresholds. We show that BiForce is more powerful and significantly faster than published tools for both binary and quantitative traits in a series of performance tests on simulated and real datasets. We demonstrate BiForce in analysing eight metabolic traits in a GWAS cohort (323 697 SNPs, >4500 individuals) and two disease traits in another (>340 000 SNPs, >1750 cases and 1500 controls) on a 32-node computing cluster. BiForce completed analyses of the eight metabolic traits within 1 day, identified nine epistatic pairs of SNPs in five metabolic traits and 18 SNP pairs in two disease traits. BiForce can make the analysis of epistasis a routine exercise in GWAS and thus improve our understanding of the role of epistasis in the genetic regulation of complex traits. Availability and implementation: The software is free and can be downloaded from http://bioinfo.utu.fi/BiForce/. Contact: wenhua.wei@igmm.ed.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.
登录
查看更多内容
DOI：
10.1038/nrg2579
发表时间：
2009-06
期刊：
Nature reviews. Genetics
影响因子：
--
作者：
Cordell HJ
通讯作者：
Cordell HJ
影响因子：
4.5
作者：
Evans, David M.;Marchini, Jonathan;Morris, Andrew P.;Cardon, Lon R.
通讯作者：
Cardon, Lon R.
DOI：
10.1038/ejhg.2010.196
发表时间：
2011-04-01
期刊：
European journal of human genetics : EJHG
影响因子：
--
作者：
Kam-Thong, Tony;Czamara, Darina;Muller-Myhsok, Bertram
通讯作者：
Muller-Myhsok, Bertram
影响因子：
5
作者：
Gauderman, WJ
通讯作者：
Gauderman, WJ
DOI：
10.1073/pnas.0903103106
发表时间：
2009-06-09
影响因子：
11.1
作者：
Hindorff, Lucia A.;Sethupathy, Praveen;Manolio, Teri A.
通讯作者：
Manolio, Teri A.