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一种整合性的多背景门德尔随机化方法,用于在人类组织中识别风险基因

Yihao Lu1, Ke Xu2, Nathaniel Maydanchik1

  • 1Department of Public Health Sciences, The University of Chicago, Chicago, IL, USA.

American journal of human genetics
|July 25, 2024
PubMed
概括

门德尔随机化 (MR) 方法在表达定量特征位点 (eQTL) 方面面临挑战,原因是有限的可用性和组织特异性. 新的mintMR框架整合了多组织eQTL数据,以在复杂的特征中进行可靠的因果推断.

关键词:
门德尔的随机化仪器变量是指仪器变量.多视图学习多视图学习多变量的多变量.类型的类型.组织特异性影响 组织特异性影响转录组范围内的孟德尔随机化.

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