popSTR2 enables clinical and population-scale genotyping of microsatellites

dc.contributorReykjavík University (RU)en_US
dc.contributorHáskólinn í Reykjavík (HR)en_US
dc.contributor.authorKristmundsdottir, Snædis
dc.contributor.authorEggertsson, Hannes P
dc.contributor.authorArnadottir, Gudny A
dc.contributor.authorHalldórsson, Bjarni
dc.contributor.departmentVerkfræðideild (HR)en_US
dc.contributor.departmentDepartment of Engineering (RU)en_US
dc.contributor.schoolTæknisvið (HR)en_US
dc.contributor.schoolSchool of Technology (RU)en_US
dc.date.accessioned2021-07-02T12:54:39Z
dc.date.available2021-07-02T12:54:39Z
dc.date.issued2019-12-05
dc.description.abstractSummary: popSTR2 is an update and augmentation of our previous work ‘popSTR: a population-based microsatellite genotyper’. To make genotyping sensitive to inter-sample differences, we supply a kernel to estimate sample-specific slippage rates. For clinical sequencing purposes, a panel of known pathogenic repeat expansions is provided along with a script that scans and flags for manual inspection markers indicative of a pathogenic expansion. Like its predecessor, popSTR2 allows for joint genotyping of samples at a population scale. We now provide a binning method that makes the microsatellite genotypes more amenable to analysis within standard association pipelines and can increase association power. Availability and implementation: https://github.com/DecodeGenetics/popSTR. Contact: snaedisk@decode.is or bjarni.halldorsson@decode.is Supplementary information: Supplementary data are available at Bioinformatics online.en_US
dc.description.versionPeer Reviewed (ritrýnd grein)en_US
dc.format.extent2269-2271en_US
dc.identifier.citationKristmundsdottir, S., Eggertsson, H. P., Arnadottir, G. A. og Halldorsson, B. V. (2020). popSTR2 enables clinical and population-scale genotyping of microsatellites. Bioinformatics, 36(7), 2269–2271. https://doi.org/10.1093/bioinformatics/btz913en_US
dc.identifier.doihttps://doi.org/10.1093/bioinformatics/btz913
dc.identifier.issn1367-4803
dc.identifier.issn1460-2059
dc.identifier.journalBioinformaticsen_US
dc.identifier.urihttps://hdl.handle.net/20.500.11815/2646
dc.language.isoenen_US
dc.publisherOxford University Press (OUP)en_US
dc.relation.ispartofseriesBioinformatics;36(7)
dc.relation.urlhttps://academic.oup.com/bioinformatics/article/36/7/2269/5658624en_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectStatistics and Probabilityen_US
dc.subjectComputational Theory and Mathematicsen_US
dc.subjectBiochemistryen_US
dc.subjectMolecular Biologyen_US
dc.subjectComputational Mathematicsen_US
dc.subjectComputer Science Applicationsen_US
dc.subjectLíkindafræðien_US
dc.subjectTölfræðien_US
dc.subjectTölvunarfræðien_US
dc.subjectLífefnafræðien_US
dc.subjectSameindalíffræðien_US
dc.titlepopSTR2 enables clinical and population-scale genotyping of microsatellitesen_US
dc.typeinfo:eu-repo/semantics/articleen_US
dcterms.licenseVC The Author(s) 2019. Published by Oxford University Press. 2269 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.en_US

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