Abstract
With the increasing availability of functional genomic data (Consortium et al., 2012, Kundaje et al., 2015, Ardlie et al., 2015), incorporating genomic annotations into QTL mapping has become a standard analytical procedure. However, the existing analysis methods often lack rigor and/or computational efficiency. We present a novel algorithm to perform integrative multi-SNP QTL mapping in a probabilistic hierarchical model framework that enables accurate and efficient joint enrichment analysis and the identification of multiple causal variants.
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