{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T04:10:20Z","timestamp":1789963820289,"version":"4.0.1"},"reference-count":43,"publisher":"Oxford University Press (OUP)","issue":"13","license":[{"start":{"date-parts":[[2016,10,12]],"date-time":"2016-10-12T00:00:00Z","timestamp":1476230400000},"content-version":"vor","delay-in-days":219,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,7,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Motivation: Although Genome Wide Association Studies (GWAS) genotype a very large number of single nucleotide polymorphisms (SNPs), the data are often analyzed one SNP at a time. The low predictive power of single SNPs, coupled with the high significance threshold needed to correct for multiple testing, greatly decreases the power of GWAS.<\/jats:p>\n                  <jats:p>Results: We propose a procedure in which all the SNPs are analyzed in a multiple generalized linear model, and we show its use for extremely high-dimensional datasets. Our method yields P-values for assessing significance of single SNPs or groups of SNPs while controlling for all other SNPs and the family wise error rate (FWER). Thus, our method tests whether or not a SNP carries any additional information about the phenotype beyond that available by all the other SNPs. This rules out spurious correlations between phenotypes and SNPs that can arise from marginal methods because the \u2018spuriously correlated\u2019 SNP merely happens to be correlated with the \u2018truly causal\u2019 SNP. In addition, the method offers a data driven approach to identifying and refining groups of SNPs that jointly contain informative signals about the phenotype. We demonstrate the value of our method by applying it to the seven diseases analyzed by the Wellcome Trust Case Control Consortium (WTCCC). We show, in particular, that our method is also capable of finding significant SNPs that were not identified in the original WTCCC study, but were replicated in other independent studies.<\/jats:p>\n                  <jats:p>Availability and implementation: Reproducibility of our research is supported by the open-source Bioconductor package hierGWAS.<\/jats:p>\n                  <jats:p>Contact: \u00a0peter.buehlmann@stat.math.ethz.ch<\/jats:p>\n                  <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btw128","type":"journal-article","created":{"date-parts":[[2016,3,8]],"date-time":"2016-03-08T20:38:23Z","timestamp":1457469503000},"page":"1990-2000","source":"Crossref","is-referenced-by-count":42,"title":["Assessing statistical significance in multivariable genome wide association analysis"],"prefix":"10.1093","volume":"32","author":[{"given":"Laura","family":"Buzdugan","sequence":"first","affiliation":[{"name":"1 Seminar for Statistics, Department of Mathematics, ETH Z\u00fcrich, Z\u00fcrich 8092, Switzerland"},{"name":"2 Department of Economics, University of Z\u00fcrich, Z\u00fcrich 8006, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Markus","family":"Kalisch","sequence":"additional","affiliation":[{"name":"1 Seminar for Statistics, Department of Mathematics, ETH Z\u00fcrich, Z\u00fcrich 8092, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arcadi","family":"Navarro","sequence":"additional","affiliation":[{"name":"3 Institute of Evolutionary Biology (CSIC-UPF), Universitat Pompeu Fabra, Barcelona 08003, Spain"},{"name":"4 Instituci\u00f3 Catalana de Recerca i Estudis Avan\u00e7ats (ICREA)"},{"name":"5 Center for Genomic Regulation (CRG), Barcelona Biomedical Research Park (PRBB), Barcelona 08003, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel","family":"Schunk","sequence":"additional","affiliation":[{"name":"6 Department of Economics, University of Mainz, Mainz, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ernst","family":"Fehr","sequence":"additional","affiliation":[{"name":"2 Department of Economics, University of Z\u00fcrich, Z\u00fcrich 8006, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peter","family":"B\u00fchlmann","sequence":"additional","affiliation":[{"name":"1 Seminar for Statistics, Department of Mathematics, ETH Z\u00fcrich, Z\u00fcrich 8092, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2016,3,7]]},"reference":[{"key":"2023020112341833900_btw128-B1","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1002\/gepi.21698","article-title":"Performance and robustness of penalized and unpenalized methods for genetic prediction of complex human disease","volume":"37","author":"Abraham","year":"2013","journal-title":"Genet. 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