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dc.contributor OTKA:K104586
dc.contributor.author Pipek, Orsolya Anna
dc.contributor.author Ribli, Dezső
dc.contributor.author Molnár, János
dc.contributor.author Póti Á
dc.contributor.author Krzystanek M
dc.contributor.author Bodor, András
dc.contributor.author Tusnády, Gábor
dc.contributor.author Szállási, Zoltán
dc.contributor.author Csabai, István
dc.contributor.author Szüts, Dávid
dc.date.accessioned 2018-06-07T08:33:33Z
dc.date.available 2018-06-07T08:33:33Z
dc.date.issued 2017
dc.identifier 85011015299
dc.identifier.citation pagination=73, pages: 11; journalVolume=18; journalIssueNumber=1; journalTitle=BMC BIOINFORMATICS;
dc.identifier.uri http://repo.lib.semmelweis.hu//handle/123456789/5556
dc.identifier.uri doi:10.1186/s12859-017-1492-4
dc.description.abstract Background: Detection of somatic mutations is one of the main goals of next generation DNA sequencing. A wide range of experimental systems are available for the study of spontaneous or environmentally induced mutagenic processes. However, most of the routinely used mutation calling algorithms are not optimised for the simultaneous analysis of multiple samples, or for non-human experimental model systems with no reliable databases of common genetic variations. Most standard tools either require numerous in-house post filtering steps with scarce documentation or take an unpractically long time to run. To overcome these problems, we designed the streamlined IsoMut tool which can be readily adapted to experimental scenarios where the goal is the identification of experimentally induced mutations in multiple isogenic samples. Methods: Using 30 isogenic samples, reliable cohorts of validated mutations were created for testing purposes. Optimal values of the filtering parameters of IsoMut were determined in a thorough and strict optimization procedure based on these test sets. Results: We show that IsoMut, when tuned correctly, decreases the false positive rate compared to conventional tools in a 30 sample experimental setup; and detects not only single nucleotide variations, but short insertions and deletions as well. IsoMut can also be run more than a hundred times faster than the most precise state of art tool, due its straightforward and easily understandable filtering algorithm. Conclusions: IsoMut has already been successfully applied in multiple recent studies to find unique, treatment induced mutations in sets of isogenic samples with very low false positive rates. These types of studies provide an important contribution to determining the mutagenic effect of environmental agents or genetic defects, and IsoMut turned out to be an invaluable tool in the analysis of such data. © 2017 The Author(s).
dc.relation.ispartof urn:issn:1471-2105
dc.title Fast and accurate mutation detection in whole genome sequences of multiple isogenic samples with IsoMut
dc.type Journal Article
dc.date.updated 2018-06-06T13:17:32Z
dc.language.rfc3066 en
dc.identifier.mtmt 3187871
dc.identifier.wos 000397487800002
dc.identifier.pubmed 28143617
dc.contributor.department SE/AOK/I/II. Sz. Patológiai Intézet
dc.contributor.institution Semmelweis Egyetem


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