{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,5,3]],"date-time":"2024-05-03T23:40:55Z","timestamp":1714779655190},"reference-count":6,"publisher":"Oxford University Press (OUP)","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2011,1,15]]},"abstract":"Abstract<\/jats:title>\n Motivation: Bioinformatics researchers have a variety of programming languages and architectures at their disposal, and recent advances in graphics processing unit (GPU) computing have added a promising new option. However, many performance comparisons inflate the actual advantages of GPU technology. In this study, we carry out a realistic performance evaluation of SNPrank, a network centrality algorithm that ranks single nucleotide polymorhisms (SNPs) based on their importance in the context of a phenotype-specific interaction network. Our goal is to identify the best computational engine for the SNPrank web application and to provide a variety of well-tested implementations of SNPrank for Bioinformaticists to integrate into their research.<\/jats:p>\n Results: Using SNP data from the Wellcome Trust Case Control Consortium genome-wide association study of Bipolar Disorder, we compare multiple SNPrank implementations, including Python, Matlab and Java as well as CPU versus GPU implementations. When compared with na\u00efve, single-threaded CPU implementations, the GPU yields a large improvement in the execution time. However, with comparable effort, multi-threaded CPU implementations negate the apparent advantage of GPU implementations.<\/jats:p>\n Availability: The SNPrank code is open source and available at http:\/\/insilico.utulsa.edu\/snprank.<\/jats:p>\n Contact: \u00a0brett.mckinney@gmail.com<\/jats:p>","DOI":"10.1093\/bioinformatics\/btq638","type":"journal-article","created":{"date-parts":[[2010,11,27]],"date-time":"2010-11-27T01:19:15Z","timestamp":1290820755000},"page":"284-285","source":"Crossref","is-referenced-by-count":11,"title":["Real-world comparison of CPU and GPU implementations of SNPrank: a network analysis tool for GWAS"],"prefix":"10.1093","volume":"27","author":[{"given":"Nicholas A.","family":"Davis","sequence":"first","affiliation":[{"name":"Department of Mathematical and Computer Sciences, University of Tulsa, Tulsa, OK 74104, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ahwan","family":"Pandey","sequence":"additional","affiliation":[{"name":"Department of Mathematical and Computer Sciences, University of Tulsa, Tulsa, OK 74104, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"B. A.","family":"McKinney","sequence":"additional","affiliation":[{"name":"Department of Mathematical and Computer Sciences, University of Tulsa, Tulsa, OK 74104, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2010,11,25]]},"reference":[{"key":"2023012512175807700_B1","doi-asserted-by":"crossref","first-page":"661","DOI":"10.1038\/nature05911","article-title":"Genome-wide association study of 14 000 cases of seven common diseases and 3000 shared controls","volume":"447","author":"Burton","year":"2007","journal-title":"Nature"},{"key":"2023012512175807700_B2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/SC.2008.5222004","article-title":"Stencil computation optimization and auto-tuning on state-of-the-art multicore architectures","volume-title":"2008 SC - International Conference for High Performance Computing, Networking, Storage and Analysis","author":"Datta","year":"2008"},{"key":"2023012512175807700_B3","doi-asserted-by":"crossref","DOI":"10.1038\/gene.2010.37","article-title":"Surfing a genetic association interaction network to identify modulators of antibody response to smallpox vaccine","author":"Davis","year":"2010","journal-title":"Genes Immun."},{"key":"2023012512175807700_B4","doi-asserted-by":"crossref","first-page":"e1000432","DOI":"10.1371\/journal.pgen.1000432","article-title":"Capturing the spectrum of interaction effects in genetic association studies by simulated evaporative cooling network analysis","volume":"5","author":"McKinney","year":"2009","journal-title":"PLoS Genet."},{"key":"2023012512175807700_B5","doi-asserted-by":"crossref","first-page":"559","DOI":"10.1086\/519795","article-title":"PLINK: A tool set for whole-genome association and population-based linkage analyses","volume":"81","author":"Purcell","year":"2007","journal-title":"Am. 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Notes"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/27\/2\/284\/48869364\/bioinformatics_27_2_284.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/27\/2\/284\/48869364\/bioinformatics_27_2_284.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,25]],"date-time":"2023-01-25T14:54:30Z","timestamp":1674658470000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/27\/2\/284\/285785"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2010,11,25]]},"references-count":6,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2011,1,15]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btq638","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2011,1,15]]},"published":{"date-parts":[[2010,11,25]]}}}