[3P-0708] Leveraging supervised learning for functionally informed fine-mapping of cis-eQTLs identifies an additional 20,913 putative causal eQTLs

^○Qingbo Wang^{1, 2, 3, 4}, David Kelley⁵, Jacob Ulirsch^{2, 3, 6}, Masahiro Kanai^{1, 2, 3, 4}, Shuvom Sadhuka^{2, 7}, Ran Cui^{2, 3}, Carlos Albors^{2, 3}, Nathan Cheng^{2, 3}, Yukinori Okada^{1, 8, 9}, Project The Biobank Japan¹⁰, Francois Aguet², Kristin Ardlie², Daniel MacArthur^{11, 12}, Hilary Finucane^{2, 3} (1.Dept. of Stat. Gen., Grad. Sch. of Med, Osaka Univ., 2.Broad Institute of MIT and Harvard, 3.Analytic and Translational Gen. Unit, Massachusetts General Hospital, 4.PhD prog. in Bioinfo. and Integ. Gen., Harvard Med. School, 5.Calico Life Sciences, 6.ハーバードメディカルスクール・生命科学, 7.Harvard College, 8.IFReC., Osaka Univ., 9.Inst. for Open and Transdisciplinary Res. Init., Osaka Univ., 10.Inst. of Med. Sci., Univ. of Tokyo, 11.Centre for Pop. Gen., Garvan Inst. of Med. Res., 12.Centre for Pop. Gen., Murdoch Children's Res. Inst.)

f . Omics(5 . Information / System / Technology)