BridGE:一种基于途径的分析工具,用于检测来自GWAS的遗传相互作用
Mehrad Hajiaghabozorgi1, Mathew Fischbach1,2, Michael Albrecht1
1Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, USA.
Nature protocols
|March 22, 2024
概括
桥梁基因组与表观症 (Bridging Gene sets with Epistasis,简称BridGE) 通过全基因组关联研究 (GWAS) 数据来确定生物途径之间的遗传相互作用. 这种新的计算方法提高了检测人类疾病复杂遗传影响的能力.
科学领域:
- 遗传学 是一个遗传学.
- 计算生物学 计算生物学
- 生物信息学是一种生物信息学.
背景情况:
- 遗传相互作用可以影响人类的表型和疾病.
- 传统的全基因组关联研究 (GWAS) 方法缺乏检测这些相互作用的统计能力.
- 识别通路级遗传相互作用对于理解复杂疾病至关重要.
研究的目的:
- 介绍桥接基因组与Epistasis (BridGE),一种新的计算方法.
- 通过使用GWAS数据,使生物途径之间的遗传相互作用能够被发现.
- 为基因相互作用分析提供强大而高效的工具.
主要方法:
- 开发了一个基于Python的BridGE管道的实现.
- 集成的数据处理,质量控制和网络建设.
- 采用通过样本变换的途径级相互作用测量和统计显著性评估.
- 在多核和多节点计算环境中启用并行处理.
主要成果:
- 桥梁促进从GWAS数据的途径层面发现遗传相互作用.
- 软件管道被优化为在典型的人类GWAS队列 (在10个节点集群上<24小时) 上高效执行.
- 标准化输出格式是为了用户的可访问性而生成的.
结论:
- 桥梁提供了一个统计学上强大的方法来识别遗传相互作用错过了传统方法.
- 该计算工具增强了对人类疾病遗传结构的理解.
- 可访问的实施和高效的性能使BridGE适合大规模GWAS分析.
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