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BiForce 工具包:全基因组关联研究中基因-基因相互作用的强大高通量计算分析。

BiForce Toolbox: powerful high-throughput computational analysis of gene-gene interactions in genome-wide association studies.

机构信息

Finnish Microarray and Sequencing Centre, Turku Centre for Biotechnology, University of Turku, Turku, Finland.

出版信息

Nucleic Acids Res. 2012 Jul;40(Web Server issue):W628-32. doi: 10.1093/nar/gks550. Epub 2012 Jun 11.

DOI:10.1093/nar/gks550
PMID:22689639
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3394281/
Abstract

Genome-wide association studies (GWAS) have discovered many loci associated with common disease and quantitative traits. However, most GWAS have not studied the gene-gene interactions (epistasis) that could be important in complex trait genetics. A major challenge in analysing epistasis in GWAS is the enormous computational demands of analysing billions of SNP combinations. Several methods have been developed recently to address this, some using computers equipped with particular graphical processing units, most restricted to binary disease traits and all poorly suited to general usage on the most widely used operating systems. We have developed the BiForce Toolbox to address the demand for high-throughput analysis of pairwise epistasis in GWAS of quantitative and disease traits across all commonly used computer systems. BiForce Toolbox is a stand-alone Java program that integrates bitwise computing with multithreaded parallelization and thus allows rapid full pairwise genome scans via a graphical user interface or the command line. Furthermore, BiForce Toolbox incorporates additional tests of interactions involving SNPs with significant marginal effects, potentially increasing the power of detection of epistasis. BiForce Toolbox is easy to use and has been applied in multiple studies of epistasis in large GWAS data sets, identifying interesting interaction signals and pathways.

摘要

全基因组关联研究(GWAS)已经发现了许多与常见疾病和数量性状相关的基因座。然而,大多数 GWAS 并未研究基因-基因相互作用(上位性),而这些相互作用在复杂性状遗传中可能很重要。分析 GWAS 中的上位性的主要挑战是分析数十亿个 SNP 组合的巨大计算需求。最近已经开发了几种方法来解决这个问题,其中一些使用配备特定图形处理单元的计算机,大多数仅限于二进制疾病性状,并且都不适合在最广泛使用的操作系统上进行通用使用。我们开发了 BiForce 工具箱来满足对高通量分析 GWAS 中数量性状和疾病性状的成对上位性的需求,这些分析适用于所有常用的计算机系统。BiForce 工具箱是一个独立的 Java 程序,它将位运算与多线程并行化相结合,从而允许通过图形用户界面或命令行快速进行全基因组扫描。此外,BiForce 工具箱还包含了对具有显著边缘效应的 SNP 相互作用的额外测试,这可能会增加检测上位性的能力。BiForce 工具箱易于使用,并已应用于多个大型 GWAS 数据集的上位性研究中,确定了有趣的相互作用信号和途径。

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本文引用的文献

1
Genome-wide analysis of epistasis in body mass index using multiple human populations.利用多个人类群体进行全基因组分析体重指数的上位性。
Eur J Hum Genet. 2012 Aug;20(8):857-62. doi: 10.1038/ejhg.2012.17. Epub 2012 Feb 15.
2
The mystery of missing heritability: Genetic interactions create phantom heritability.遗传力缺失之谜:基因相互作用产生了幽灵遗传力。
Proc Natl Acad Sci U S A. 2012 Jan 24;109(4):1193-8. doi: 10.1073/pnas.1119675109. Epub 2012 Jan 5.
3
Characterisation of genome-wide association epistasis signals for serum uric acid in human population isolates.
一项针对欧洲人群肺癌易感性的全基因组基因-基因交互作用的大规模研究,在亚洲人群中进行了跨种族验证。
J Thorac Oncol. 2022 Aug;17(8):974-990. doi: 10.1016/j.jtho.2022.04.011. Epub 2022 Apr 30.
4
Recessive/dominant model: Alternative choice in case-control-based genome-wide association studies.隐性/显性模型:基于病例对照的全基因组关联研究的另一种选择。
PLoS One. 2021 Jul 21;16(7):e0254947. doi: 10.1371/journal.pone.0254947. eCollection 2021.
5
A parallelized strategy for epistasis analysis based on Empirical Bayesian Elastic Net models.基于经验贝叶斯弹性网络模型的上位性分析并行策略。
Bioinformatics. 2020 Jun 1;36(12):3803-3810. doi: 10.1093/bioinformatics/btaa216.
6
Clinical Implications of Single Nucleotide Polymorphisms in Diagnosis of Asthma and its Subtypes.单核苷酸多态性在哮喘及其亚型诊断中的临床意义
Yonsei Med J. 2019 Jan;60(1):1-9. doi: 10.3349/ymj.2019.60.1.1.
7
pulver: an R package for parallel ultra-rapid p-value computation for linear regression interaction terms.Pulver:一个用于线性回归交互项并行超快速p值计算的R包。
BMC Bioinformatics. 2017 Sep 29;18(1):429. doi: 10.1186/s12859-017-1838-y.
8
CollapsABEL: an R library for detecting compound heterozygote alleles in genome-wide association studies.CollapsABEL:一个用于在全基因组关联研究中检测复合杂合子等位基因的R语言库。
BMC Bioinformatics. 2016 Apr 8;17:156. doi: 10.1186/s12859-016-1006-9.
9
Detecting epistasis in human complex traits.检测人类复杂性状中的上位性。
Nat Rev Genet. 2014 Nov;15(11):722-33. doi: 10.1038/nrg3747. Epub 2014 Sep 9.
10
Abundant local interactions in the 4p16.1 region suggest functional mechanisms underlying SLC2A9 associations with human serum uric acid.4p16.1区域丰富的局部相互作用提示了SLC2A9与人类血清尿酸关联背后的功能机制。
Hum Mol Genet. 2014 Oct 1;23(19):5061-8. doi: 10.1093/hmg/ddu227. Epub 2014 May 12.
人类群体分离物中血清尿酸全基因组关联上位性信号的特征描述。
PLoS One. 2011;6(8):e23836. doi: 10.1371/journal.pone.0023836. Epub 2011 Aug 19.
4
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Nat Genet. 2011 Jul 10;43(8):761-7. doi: 10.1038/ng.873.
5
The meta-analysis of genome-wide association studies.全基因组关联研究的荟萃分析。
Brief Bioinform. 2011 May;12(3):259-69. doi: 10.1093/bib/bbr020.
6
EpiGPU: exhaustive pairwise epistasis scans parallelized on consumer level graphics cards.EpiGPU:在消费级显卡上并行执行的详尽成对上位性扫描。
Bioinformatics. 2011 Jun 1;27(11):1462-5. doi: 10.1093/bioinformatics/btr172. Epub 2011 Apr 6.
7
Genome-wide interaction-based association analysis identified multiple new susceptibility Loci for common diseases.基于全基因组相互作用的关联分析鉴定出常见疾病的多个新易感位点。
PLoS Genet. 2011 Mar;7(3):e1001338. doi: 10.1371/journal.pgen.1001338. Epub 2011 Mar 17.
8
GBOOST: a GPU-based tool for detecting gene-gene interactions in genome-wide case control studies.GBOOST:一种基于 GPU 的工具,用于在全基因组病例对照研究中检测基因-基因相互作用。
Bioinformatics. 2011 May 1;27(9):1309-10. doi: 10.1093/bioinformatics/btr114. Epub 2011 Mar 3.
9
EPIBLASTER-fast exhaustive two-locus epistasis detection strategy using graphical processing units.利用图形处理单元的 EPIBLASTER——快速穷尽双基因座上位性检测策略。
Eur J Hum Genet. 2011 Apr;19(4):465-71. doi: 10.1038/ejhg.2010.196. Epub 2010 Dec 8.
10
Analysing biological pathways in genome-wide association studies.全基因组关联研究中的生物途径分析。
Nat Rev Genet. 2010 Dec;11(12):843-54. doi: 10.1038/nrg2884.