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Chunk #42 — Methods — Expression genome-wide association study (eGWAS) — Statistical methods for eGWAS

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Brain expression genome-wide association study (eGWAS) identifies human disease-associated variants.
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Linear regression analysis to test for cisSNP/transcript associations were done in PLINK [58]. Preprocessed probe transcript levels were utilized as endophenotypes. Each probe was assessed separately, even though one gene may have multiple probes. CisSNPs localized to ±100 kb flanking region of the gene targeted by the probe of interest, mapped according to NCBI Build 36, were assessed for transcript level associations, using an additive model, with the minor allele dosage (0, 1, 2) as the independent variable, and APOE ε4 dosage (0, 1, 2), age at death, gender, PCR plate, RIN, (RIN-RINmean)2 as covariates. The cerebellum and temporal cortex expression levels were analyzed separately. The ADs and non–ADs were analyzed both separately and jointly. The joint analyses included diagnosis as an additional covariate (AD = 1, non–AD = 0). We also ran analyses including the top 10 eigenvectors from EIGENSTRAT, and compared eGWAS results to those excluding the eigenvectors (Text S1, Figure S8, Supplementary Table 27 in Dataset S1) [59].