Discovery and refinement of genetic loci associated with cardiometabolic risk using dense imputation maps

Discovery and refinement of genetic loci associated with cardiometabolic risk using dense imputation maps

<p>Large-scale whole genome sequence datasets offer novel opportunities to identify genetic variation underlying human traits. Here we apply genotype imputation based on whole genome sequence data from the UK10K and the 1000 Genomes Projects into 35,981 study participants of European ancestry,...

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Main Authors: Iotchkova, V, Huang, J, Morris, J, Jain, D, Barbieri, C, Walter, K, Min, J, Chen, L, Astle, W, Cocca, M, Deelen, P, Elding, H, Farmaki, A, Franklin, C, Franberg, M, Gaunt, T, Hofman, A, Jiang, T, Kleber, M, Lachance, G, Luan, J, Malerba, G, Matchan, A, Mead, D, Memari, Y, Ntalla, I, Panoutsopoulou, K, Pazoki, R, Perry, J, Rivadeneira, F, Sabater-Lleal, M, Sennblad, B, Shin, S, Southam, L, Traglia, M, van Dijk, F, van Leeuwen, E, Zaza, G, Zhang, W, Amin, N, Butterworth, A, Chambers, J, Dedoussis, G, Dehghan, A, Franco, O, Franke, L, Frontini, M, Gambaro, G, Gasparini, P, Hamsten, A, Issacs, A, Kooner, J, Kooperberg, C, Langenberg, C, Marz, W, Scott, R, Swertz, M, Toniolo, D, Uitterlinden, A, van Duijn, C, Watkins, H, Zeggini, E, Maurano, M, Timpson, N, Reiner, A, Auer, P, Soranzo, N
Format: Journal article
Language:English
Published: Nature Publishing Group 2016

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