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数据协调指导方针将来自混合群体的多平台基因组数据结合起来,并提高基因组广泛关联研究的力量

Dayna Croock¹, Yolandi Swart¹, Haiko Schurz¹

¹DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch, South Africa.

Current protocols

|June 5, 2024

概括

我们提出了来自不同种群的遗传数据合并的指导方针,改进了全基因组关联研究 (GWAS). 这种协调提高了统计能力,并纠正了混合样本中的批量效应和人口分层.

科学领域:

遗传学是一个遗传学.
生物信息学是一种生物信息学.
人口遗传学人口遗传学

背景情况:

数据协调将独立的数据集合并,以增加遗传关联测试中的统计能力.
现有的协议与批量效应,人口分层和混合祖先作斗争.
缺乏标准化,可访问的方法来协调多平台遗传数据,特别是在混合种群中.

研究的目的:

提出一套指导方针,用于从混合样本中合并多平台遗传数据.
为具有基本生物信息学技能的研究人员提供一个实用的协议.
在多样化的群体中实现强大的全基因组关联研究 (GWAS).

主要方法:

为数组基因型和全基因组测序数据制定详细的数据协调协议.
从六个数据集中合并1544例结核病 (TB) 病例控制样本的协议的应用.
使用ADMIXTURE和RFMix进行祖先推断和伪案例对照比较,以纠正批量效应.

主要成果:

成功将1544个结核病例控制样本汇总成统一的数据集.
与单个数据集分析相比,协调的GWAS显示了更好的统计能力.
总结统计没有由于批量效应和人口分层而导致的混偏差.

结论:

拟议的指导方针有助于对混合样本进行强有力的数据协调.
这种方法提高了GWAS在不同人群中的力量和准确性.
该协议可供具有基本生物信息学经验的研究人员访问,促进更广泛的采用.

关键词:

血统推断的推断是祖先的推断.批量效应批量效应批量效应数据统一和数据协调.基因组数据基因组数据公司合并,合并.

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