ABSTRACT A genetic Gaussian network of multiple phenotypes, constructed through the inverse matrix of the genetic correlation matrix, is informative for understanding the biological dependencies of the phenotypes. However, its estimation may be challenging because the genetic correlation estimates are biased due to estimation errors and idiosyncratic pleiotropy inherent in GWAS summary statistics. Here, we introduce a novel approach called estimation of genetic graph (EGG), which eliminates the estimation error bias and idiosyncratic pleiotropy bias with the same techniques used in multivariable Mendelian randomization. The genetic network estimated by EGG can be interpreted as shared common biological contributions between phenotypes, conditional on others. We use both simulations and real data to demonstrate the superior efficacy of our novel method in comparison with the traditional network estimators.

Yihe Yang

Noah Lorincz-Comi

Xiaofeng Zhu

Biometrics

国际生物统计学会是一个促进统计和数学理论和方法在生物科学领域的发展和应用的国际协会，包括农业、生物医学科学和公共卫生、生态学、环境科学、林业和相关学科。协会欢迎统计学家、数学家、生物科学家和其他致力于跨学科努力推动生物科学信息收集和解释的人士成为会员。该协会赞助在世界各地举行的两年一度的国际生物识别会议；通过其国家团体和地区，它还赞助地区和地方会议。

The International Biometric Society is an international association dedicated to promoting the development and application of statistical and mathematical theories and methods in the field of biosciences. This includes areas such as agriculture, biomedical sciences, public health, ecology, environmental science, forestry, and related disciplines. The society welcomes statisticians, mathematicians, biologists, and other professionals committed to interdisciplinary efforts to advance the collection and interpretation of bioscience information. The society sponsors a biennial International Biometric Conference held worldwide, as well as regional and local meetings through its national and regional groups.

国际生物统计学会是一个致力于促进统计学和数学理论及方法在生物科学领域的应用与发展的国际性协会。该协会涵盖多个领域，包括农业、生物医学科学、公共卫生、生态学、环境科学、林业及相关学科。协会欢迎统计学家、数学家、生物科学家及其他致力于跨学科合作、推动生物科学信息收集与解释的专业人士加入。该协会每两年举办一次国际生物识别会议，并通过其国家和地区分支机构赞助地方和区域性会议。

Category	Quartile
数学	4
数学, 生物学	3
数学, 数学与计算生物学	3
数学, 统计学与概率论	3

Estimation of a genetic Gaussian network using GWAS summary data

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Journal Info

Category	Quartile
STATISTICS & PROBABILITY	2