Topic modeling identifies novel genetic loci associated with multimorbidities in UK Biobank-Yidong Zhang et al.

Published: 24 July 2023| Version 1 | DOI: 10.17632/rft63p3jcd.1
Contributors:
yidong zhang, Xilin Jiang, Gil McVean, Gerton Lunter

Description

GWAS results for topics of common diseases inferred by treeLFA on the UK Biobank data. Decompress the attached files to see the summary statistics of GWAS for topics.

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Steps to reproduce

Topics of common diseases (encoded using the ICD-10 coding system, representing multimorbidity clusters) and individuals' weights for these topics were inferred by treeLFA from the diagnosis data in the UK Biobank. The inferred topic weights were used as continuous traits for GWAS. Logit transformation was applied to topic weights before fitting the linear regression models. Individuals' age, sex and the first ten principal components were controlled. See details in the paper "Topic modeling identifies novel genetic loci associated with multimorbidities in UK Biobank" by Yidong Zhang, et al..

Institutions

University of Oxford

Categories

Genome Wide Association Study, Summary Statistic

Funding

Chinese Academy of Medical Sciences (CAMS) Innovation Fund for Medical Science (CIFMS), China

2018-I2M-2-002

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