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Chunk #57 — ONLINE METHODS — Biological annotation.

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Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals.
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We used DEPICT19 (downloaded February 2016 from https://github.com/perslab/depict) to identify the tissues/cell types where the causal genes are strongly expressed, detect enrichment of gene sets, and prioritize likely causal genes. We ran DEPICT as described previously10 with the following exceptions: we used 37,427 human Affymetrix HGU133a2.0 platform microarrays19, discarded gene sets that were not well reconstituted42, and relaxed the significance threshold for defining a matching SNP in the simulated null GWAS from 5×10−4 to 5×10−3. “Previously prioritized” genes were prioritized by DEPICT (in the sense of achieving FDR < 0.05) both in Okbay et al.10 and in the current work; “newly prioritized genes,” on the other hand, were not prioritized in Okbay et al.10. We used expression data from the BrainSpan Developmental Transcriptome34 and calculated the average expression in the brain of all DEPICT-prioritized EduYears genes (Supplementary Table 7) as a function of developmental stage (Supplementary Table 8, Supplementary Figure 22).