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dc.contributor.authorBalzer, Susanne Mignoneng
dc.contributor.authorMalde, Ketileng
dc.contributor.authorGrohme, Markus A.eng
dc.contributor.authorJonassen, Ingeeng
dc.description.abstractMotivation: Throughout the recent years, 454 pyrosequencing has emerged as an efficient alternative to traditional Sanger sequencing and is widely used in both de novo whole-genome sequencing and metagenomics. Especially the latter application is extremely sensitive to sequencing errors and artificially duplicated reads. Both are common in 454 pyrosequencing and can create a strong bias in the estimation of diversity and composition of a sample. To date, there are several tools that aim to remove both sequencing noise and duplicates. Nevertheless, duplicate removal is often based on nucleotide sequences rather than on the underlying flow values, which contain additional information. Results: With the novel tool JATAC, we present an approach towards a more accurate duplicate removal by analysing flow values directly. Making use of previous findings on 454 flow data characteristics, we combine read clustering with Bayesian distance measures. Finally, we provide a benchmark with an existing algorithm. Availability: JATAC is freely available under the General Public License from Supplementary information: Supplementary data are available at Bioinformatics onlineen_US
dc.publisherOxford University Pressen_US
dc.relation.ispartof<a href="" target="blank">Characteristics of Pyrosequencing Data – Analysis, Methods, and Tools</a></p>en_US
dc.rightsAttribution CC BYeng
dc.titleFiltering duplicate reads from 454 pyrosequencing dataen_US
dc.typePeer reviewed
dc.typeJournal article
dc.rights.holderCopyright The Author 2013. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.en_US

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