Abstract:
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The goal of an eQTL analysis is to detect patterns of transcript expression related to specific genetic variants. In this talk we present our recently developed analysis protocol for performing extensive eQTL analyses - from raw RNA-seq reads and genotype data to eQTL plots showing gene-SNP interactions. We explain in detail how expression and genotype data are filtered, transformed, and batch corrected. We also discuss possible pitfalls and artifacts that may occur when analyzing genomic data from different sources jointly. Our protocol is tested on a publicly available data set of the RNA-seq project from the gEUVADIS consortium and also applied to recently generated omics data from the GeneSTAR project at Johns Hopkins. One goal of this project is to understand the biology of platelet aggregation. Therefore, we examined genetic and transcriptomic data from megakaryocytes (MKs), the precursor cells for anucleate platelets, that are derived from induced pluripotent stem cells (iPSCs). Given a high genetic and transcriptomic integrity of MKs, we found several hundred cis-eQTLs in European Americans and African Americans and see a high replication between the two groups.
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