{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T05:32:47Z","timestamp":1775280767722,"version":"3.50.1"},"reference-count":12,"publisher":"Oxford University Press (OUP)","issue":"24","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2012,12,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Summary: Genome-wide association studies are widely used to investigate the genetic basis of diseases and traits, but they pose many computational challenges. We developed gdsfmt and SNPRelate (R packages for multi-core symmetric multiprocessing computer architectures) to accelerate two key computations on SNP data: principal component analysis (PCA) and relatedness analysis using identity-by-descent measures. The kernels of our algorithms are written in C\/C++ and highly optimized. Benchmarks show the uniprocessor implementations of PCA and identity-by-descent are \u223c8\u201350 times faster than the implementations provided in the popular EIGENSTRAT (v3.0) and PLINK (v1.07) programs, respectively, and can be sped up to 30\u2013300-fold by using eight cores. SNPRelate can analyse tens of thousands of samples with millions of SNPs. For example, our package was used to perform PCA on 55 324 subjects from the \u2018Gene-Environment Association Studies\u2019 consortium studies.<\/jats:p>\n               <jats:p>Availability and implementation: gdsfmt and SNPRelate are available from R CRAN (http:\/\/cran.r-project.org), including a vignette. A tutorial can be found at https:\/\/www.genevastudy.org\/Accomplishments\/software.<\/jats:p>\n               <jats:p>Contact: \u00a0zhengx@u.washington.edu<\/jats:p>","DOI":"10.1093\/bioinformatics\/bts606","type":"journal-article","created":{"date-parts":[[2012,10,12]],"date-time":"2012-10-12T00:24:35Z","timestamp":1350001475000},"page":"3326-3328","source":"Crossref","is-referenced-by-count":2392,"title":["A high-performance computing toolset for relatedness and principal component analysis of SNP data"],"prefix":"10.1093","volume":"28","author":[{"given":"Xiuwen","family":"Zheng","sequence":"first","affiliation":[{"name":"Department of Biostatistics, University of Washington, Seattle, WA 98195-7232, USA"}]},{"given":"David","family":"Levine","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, University of Washington, Seattle, WA 98195-7232, USA"}]},{"given":"Jess","family":"Shen","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, University of Washington, Seattle, WA 98195-7232, USA"}]},{"given":"Stephanie M.","family":"Gogarten","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, University of Washington, Seattle, WA 98195-7232, USA"}]},{"given":"Cathy","family":"Laurie","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, University of Washington, Seattle, WA 98195-7232, USA"}]},{"given":"Bruce S.","family":"Weir","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, University of Washington, Seattle, WA 98195-7232, USA"}]}],"member":"286","published-online":{"date-parts":[[2012,10,11]]},"reference":[{"key":"2023012513244457500_bts606-B1","doi-asserted-by":"crossref","first-page":"1061","DOI":"10.1038\/nature09534","article-title":"A map of human genome variation from population-scale sequencing","volume":"467","author":"1000 Genomes Project Consortium","year":"2010","journal-title":"Nature"},{"key":"2023012513244457500_bts606-B2","doi-asserted-by":"crossref","first-page":"598","DOI":"10.1016\/S0140-6736(03)12520-2","article-title":"Population stratification and spurious allelic association","volume":"361","author":"Cardon","year":"2003","journal-title":"Lancet"},{"key":"2023012513244457500_bts606-B3","doi-asserted-by":"crossref","first-page":"668","DOI":"10.1002\/gepi.20418","article-title":"Case-control association testing in the presence of unknown relationships","volume":"33","author":"Choi","year":"2009","journal-title":"Genet Epidemiol."},{"key":"2023012513244457500_bts606-B4","doi-asserted-by":"crossref","first-page":"364","DOI":"10.1002\/gepi.20492","article-title":"The gene, environment association studies consortium (GENEVA): maximizing the knowledge obtained from gwas by collaboration across studies of multiple conditions","volume":"34","author":"Cornelis","year":"2010","journal-title":"Genet Epidemiol."},{"key":"2023012513244457500_bts606-B5","doi-asserted-by":"crossref","first-page":"2156","DOI":"10.1093\/bioinformatics\/btr330","article-title":"The variant call format and vcftools","volume":"27","author":"Danecek","year":"2011","journal-title":"Bioinformatics"},{"key":"2023012513244457500_bts606-B6","doi-asserted-by":"crossref","DOI":"10.1093\/bioinformatics\/bts610","article-title":"GWASTools: an R\/Bioconductor package for quality control and analysis of genome-wide association studies","author":"Gogarten","year":"2012","journal-title":"Bioinformatics"},{"key":"2023012513244457500_bts606-B7","doi-asserted-by":"crossref","first-page":"591","DOI":"10.1002\/gepi.20516","article-title":"Quality control and quality assurance in genotypic data for genome-wide association studies","volume":"34","author":"Laurie","year":"2010","journal-title":"Genet Epidemiol."},{"key":"2023012513244457500_bts606-B8","doi-asserted-by":"crossref","first-page":"1153","DOI":"10.1093\/genetics\/163.3.1153","article-title":"Maximum-likelihood estimation of relatedness","volume":"163","author":"Milligan","year":"2003","journal-title":"Genetics"},{"key":"2023012513244457500_bts606-B9","doi-asserted-by":"crossref","first-page":"904","DOI":"10.1038\/ng1847","article-title":"Principal components analysis corrects for stratification in genome-wide association studies","volume":"38","author":"Price","year":"2006","journal-title":"Nat. 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Genet."}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/28\/24\/3326\/48879518\/bioinformatics_28_24_3326.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/28\/24\/3326\/48879518\/bioinformatics_28_24_3326.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,25]],"date-time":"2023-01-25T19:22:01Z","timestamp":1674674521000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/28\/24\/3326\/245844"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012,10,11]]},"references-count":12,"journal-issue":{"issue":"24","published-print":{"date-parts":[[2012,12,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/bts606","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2012,12]]},"published":{"date-parts":[[2012,10,11]]}}}