Topic modeling identifies novel genetic loci associated with multimorbidities in UK Biobank-Yidong Zhang et al.
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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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..
Chinese Academy of Medical Sciences (CAMS) Innovation Fund for Medical Science (CIFMS), China