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dc.contributor.authorHighnam, Garethen
dc.contributor.authorFranck, Christopher T.en
dc.contributor.authorMartin, Andyen
dc.contributor.authorStephens, Calvinen
dc.contributor.authorPuthige, Ashwinen
dc.contributor.authorMittelman, Daviden
dc.date.accessioned2019-04-15T14:27:15Zen
dc.date.available2019-04-15T14:27:15Zen
dc.date.issued2013-01en
dc.identifier.citationNVIDIA Foundation’s ‘Compute the Cure’ program (to D.M.). Funding for open access charge: NIH.en
dc.identifier.issn0305-1048en
dc.identifier.urihttp://hdl.handle.net/10919/88962en
dc.description.abstractRepetitive sequences are biologically and clinically important because they can influence traits and disease, but repeats are challenging to analyse using short-read sequencing technology. We present a tool for genotyping microsatellite repeats called RepeatSeq, which uses Bayesian model selection guided by an empirically derived error model that incorporates sequence and read properties. Next, we apply RepeatSeq to high-coverage genomes from the 1000 Genomes Project to evaluate performance and accuracy. The software uses common formats, such as VCF, for compatibility with existing genome analysis pipelines. Source code and binaries are available at http://github.com/adaptivegenome/repeatseq.en
dc.description.sponsorshipNational Institutes of Health [NS079926]; NVIDIA Foundation; NIHen
dc.format.extent7 pagesen
dc.format.mimetypeapplication/pdfen
dc.language.isoen_USen
dc.publisherOxford University Pressen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectrepeat instabilityen
dc.subjectsequencing dataen
dc.subjectread alignmenten
dc.subjectdisordersen
dc.subjectmutationsen
dc.subjectevolutionen
dc.subjectformaten
dc.titleAccurate human microsatellite genotypes from high-throughput resequencing data using informed error profilesen
dc.typeArticle - Refereeden
dc.contributor.departmentBiological Sciencesen
dc.contributor.departmentStatisticsen
dc.contributor.departmentFralin Biomedical Research Instituteen
dc.contributor.departmentFralin Life Sciences Instituteen
dc.description.notesNational Institutes of Health [NS079926 to D. M.]; NVIDIA Foundation's 'Compute the Cure' program (to D. M.). Funding for open access charge: NIH.en
dc.title.serialNucleic Acids Researchen
dc.identifier.doihttps://doi.org/10.1093/nar/gks981en
dc.identifier.volume41en
dc.identifier.issue1en
dc.type.dcmitypeTexten
dc.identifier.pmid23090981en
dc.identifier.eissn1362-4962en


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Creative Commons Attribution 4.0 International
License: Creative Commons Attribution 4.0 International