Sequence Kernel Association Test of Multiple Continuous Phenotypes

Avery, 2011, A phenomics-based strategy identifies loci on APOC1, BRAP, and PLCG1 associated with metabolic syndrome phenotype domains, PLoS Genet, 7, e1002322, 10.1371/journal.pgen.1002322

Chen, 2014, Sequence kernel association test for survival traits, Genet Epidemiol, 38, 191, 10.1002/gepi.21791

Chen, 2013, A functional variant rs1820453 in YAP1 and breast cancer risk in Chinese population, PLoS ONE, 8, e79056, 10.1371/journal.pone.0079056

Davies, 1980, Algorithm AS 155: the distribution of a linear combination of χ2 random variables, Appl Stat, 29, 323, 10.2307/2346911

Dixit, 2014, Chaetocin-induced ROS-mediated apoptosis involves ATM-YAP1 axis and JNK-dependent inhibition of glucose metabolism, Cell Death Dis, 5, e1212, 10.1038/cddis.2014.179

Ferreira, 2009, A multivariate test of association, Bioinformatics, 25, 132, 10.1093/bioinformatics/btn563

Grove, 2013, Best practices and joint calling of the HumanExome BeadChip: the CHARGE consortium, PloS One, 8, e68095, 10.1371/journal.pone.0068095

He, 2013, A general framework for association tests with multivariate traits in large-scale genomics studies, Genet Epidemiol, 37, 759, 10.1002/gepi.21759

Hua, 2015, Equivalence of kernel machine regression and kernel distance covariance for multidimensional phenotype association studies, Biometrics, 71, 812, 10.1111/biom.12314

Kuonen, 1999, Saddlepoint approximations for distributions of quadratic forms in normal variables, Biometrika, 86, 929, 10.1093/biomet/86.4.929

Lee, 2012, Optimal tests for rare variant effects in sequencing association studies, Biostatistics, 13, 762, 10.1093/biostatistics/kxs014

Li, 2012, Identification of YAP1 as a novel susceptibility gene for polycystic ovary syndrome, J Med Genet, 49, 254, 10.1136/jmedgenet-2011-100727

Lin, 2011, A general framework for detecting disease associations with rare variants in sequencing studies, Am J Hum Genet, 89, 354, 10.1016/j.ajhg.2011.07.015

Liu, 2009a, A new chi-square approximation to the distribution of non-negative definite quadratic forms in non-central normal variables, Comput Stat Data Anal, 53, 853, 10.1016/j.csda.2008.11.025

Liu, 2009b, Bivariate association analyses for the mixture of continuous and binary traits with the use of extended generalized estimating equations, Genet Epidemiol, 33, 217, 10.1002/gepi.20372

Louwers, 2013, Cross-ethnic meta-analysis of genetic variants for polycystic ovary syndrome, J Clin Endocrinol Metab, 98, E2006, 10.1210/jc.2013-2495

Madsen, 2009, A groupwise association test for rare mutations using a weighted sum statistic, PLOS Genet, 5, e1000384, 10.1371/journal.pgen.1000384

Maity, 2012, Multivariate phenotype association analysis by marker-set kernel machine regression, Genet Epidemiol, 36, 686, 10.1002/gepi.21663

Manolio, 2009, Finding the missing heritability of complex diseases, Nature, 461, 747, 10.1038/nature08494

Morgenthaler, 2007, A strategy to discover genes that carry multi-allelic or mono-allelic risk for common diseases: a cohort allelic sums test (CAST), Mutat Res, 615, 28, 10.1016/j.mrfmmm.2006.09.003

Morris, 2010, An evaluation of statistical approaches to rare variant analysis in genetic association studies, Genet Epidemiol, 34, 188, 10.1002/gepi.20450

Neale, 2011, Testing for an unusual distribution of rare variants, PLoS Genet, 7, e1001322, 10.1371/journal.pgen.1001322

OReilly, 2012, MultiPhen: joint model of multiple phenotypes can increase discovery in GWAS, PLoS ONE, 7, e34861, 10.1371/journal.pone.0034861

Price, 2010, Pooled association tests for rare variants in exon-resequencing studies, Am J Hum Genet, 86, 832, 10.1016/j.ajhg.2010.04.005

Rasmussen-Torvik, 2010, Impact of repeated measures and sample selection on genome-wide association studies of fasting glucose, Genet Epidemiol, 34, 665, 10.1002/gepi.20525

Schaffner, 2005, Calibrating a coalescent simulation of human genome sequence variation, Genome Res, 15, 1576, 10.1101/gr.3709305

Schifano, 2013, Genome-wide association analysis for multiple continuous secondary phenotypes, Am J Human Genetics, 92, 744, 10.1016/j.ajhg.2013.04.004

Solovieff, 2013, Pleiotropy in complex traits: challenges and strategies, Nat Rev Genet, 14, 483, 10.1038/nrg3461

Stephens, 2013, A unified framework for association analysis with multiple related phenotypes, PLoS ONE, 8, e65245, 10.1371/journal.pone.0065245

The ARIC Investigators, 1989, The atherosclerosis risk in communities (aric) study: design and objectives, Am J Epidemiol, 129, 687, 10.1093/oxfordjournals.aje.a115184

Sluis, 2013, TATES: efficient multivariate genotype-phenotype analysis for genome-wide association studies, PLoS Genet, 9, e1003235, 10.1371/journal.pgen.1003235

Wu, 2015, Statistical methods for association tests of multiple continuous traits in genome-wide association studies, Ann Hum Genet, 79, 282, 10.1111/ahg.12110

Wu, 2015, Sequence kernel association analysis of rare variant set based on the marginal regression model for binary traits, Genet Epidemiol, 39, 399, 10.1002/gepi.21913

Wu, 2010, Genome-wide interrogation identifies YAP1 variants associated with survival of small-cell lung cancer patients, Cancer Res, 70, 9721, 10.1158/0008-5472.CAN-10-1493

Wu, 2010, Powerful SNP-Set analysis for case-control genome-wide association studies, Am J Hum Genet, 86, 929, 10.1016/j.ajhg.2010.05.002

Wu, 2011, Rare-variant association testing for sequencing data with the sequence kernel association test, Am J Hum Genet, 89, 82, 10.1016/j.ajhg.2011.05.029

Yang, 2010, Analyze multivariate phenotypes in genetic association studies by combining univariate association tests, Genet Epidemiol, 34, 444, 10.1002/gepi.20497