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Chunk #22 — Results — Application to meta-analysis data of lipid phenotypes

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Integrating functional data to prioritize causal variants in statistical fine-mapping studies.
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coding exons increases from 7.4 to 12.4 from using the original data to 1KG-imputed data (see Table S4). This effect is most likely due to the availability of more variants through imputation thus being able to localize the association signal to genomic annotation more accurately. Across the four traits in general, we see consistent signal of increased relative probability for causality within transcribed regions (e.g. exons and transcription start sites (TSS)) and a depletion of causal variants in repressed regions; for example, for TG, the coding exons show a log2 relative probability for causality of 3.4 while the repressed regions show an log2 relative probability of −1.6.