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PREQUAL: detecting non-homologous characters in sets of unaligned homologous sequences
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Ecology and Genetics, Evolutionary Biology.
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Organismal Biology, Systematic Biology.ORCID iD: 0000-0002-3628-1137
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Organismal Biology, Systematic Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
2018 (English)In: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 34, no 22, p. 3929-3930Article in journal (Refereed) Published
Abstract [en]

A Summary: Phylogenomic datasets invariably contain undetected stretches of non-homologous characters due to poor-quality sequences or erroneous gene models. The large-scale multi-gene nature of these datasets renders impractical or impossible detailed manual curation of sequences, but few tools exist that can automate this task. To address this issue, we developed a new method that takes as input a set of unaligned homologous sequences and uses an explicit probabilistic approach to identify and mask regions with non-homologous adjacent characters. These regions are defined as sharing no statistical support for homology with any other sequence in the set, which can result from e.g. sequencing errors or gene prediction errors creating frameshifts. Our methodology is implemented in the program PREQUAL, which is a fast and accurate tool for high-throughput filtering of sequences. The program is primarily aimed at amino acid sequences, although it can handle protein coding DNA sequences as well. It is fully customizable to allow fine-tuning of the filtering sensitivity.

Place, publisher, year, edition, pages
OXFORD UNIV PRESS , 2018. Vol. 34, no 22, p. 3929-3930
National Category
Bioinformatics and Systems Biology Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:uu:diva-371877DOI: 10.1093/bioinformatics/bty448ISI: 000450039900023PubMedID: 29868763OAI: oai:DiVA.org:uu-371877DiVA, id: diva2:1274906
Available from: 2019-01-03 Created: 2019-01-03 Last updated: 2019-01-03Bibliographically approved

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Whelan, SimonIrisarri, IkerBurki, Fabien

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