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Chunk #47 — STAR★METHODS — QUANTIFICATION AND STATISTICAL ANALYSIS — Common-factor meta-analysis

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Trans-ancestry genome-wide study of depression identifies 697 associations implicating cell types and pharmacotherapies.
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To examine the role of how MDD status was ascertained and phenotyped,69 we meta-analysed European ancestry studies together based on phenotyping approach (clinical, electronic health records, questionnaire, or self-reported diagnosis) and then analysed the grouped meta-analysis summary statistics in Genomic SEM.13 We estimated LD Score genetic correlations between each phenotype approach and conducted a common factor GWAS to test for heterogeneity in SNP effects across approaches. We fit a one-factor model where the loading factor on the Clinical/Interview phenotype was fixed to 1, so that the latent factor explains all the variance in clinical depression. We tested the hypothesis that the covariance matrix implied by the model differed from that observed in the input data.