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Article: SRinversion: a tool for detecting short inversions by splitting and re-aligning poorly mapped and unmapped sequencing reads

TitleSRinversion: a tool for detecting short inversions by splitting and re-aligning poorly mapped and unmapped sequencing reads
Authors
Issue Date2016
PublisherOxford University Press. The Journal's web site is located at http://bioinformatics.oxfordjournals.org/
Citation
Bioinformatics, 2016, v. 32, p. 3559-3565 How to Cite?
AbstractMOTIVATION: Rapid development in sequencing technologies has dramatically improved our ability to detect genetic variants in human genome. However, current methods have variable sensitivities in detecting different types of genetic variants. One type of such genetic variants that is especially hard to detect is inversions. Analysis of public databases showed that few short inversions have been reported so far. Unlike reads that contain small insertions or deletions, which will be considered through gap alignment, reads carrying short inversions often have poor mapping quality or are unmapped, thus are often not further considered. As a result, the majority of short inversions might have been overlooked and require special algorithms for their detection. RESULTS: Here, we introduce SRinversion, a framework to analyze poorly mapped or unmapped reads by splitting and re-aligning them for the purpose of inversion detection. SRinversion is very sensitive to small inversions and can detect those less than 10 bp in size. We applied SRinversion to both simulated data and high-coverage sequencing data from the 1000 Genomes Project and compared the results with those from Pindel, BreakDancer, DELLY, Gustaf and MID. A better performance of SRinversion was achieved for both datasets for the detection of small inversions.
Persistent Identifierhttp://hdl.handle.net/10722/248488
ISSN
2020 Impact Factor: 6.937
2020 SCImago Journal Rankings: 3.599
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorCHEN, R-
dc.contributor.authorLau, YL-
dc.contributor.authorZhang, Y-
dc.contributor.authorYang, W-
dc.date.accessioned2017-10-18T08:43:59Z-
dc.date.available2017-10-18T08:43:59Z-
dc.date.issued2016-
dc.identifier.citationBioinformatics, 2016, v. 32, p. 3559-3565-
dc.identifier.issn1367-4803-
dc.identifier.urihttp://hdl.handle.net/10722/248488-
dc.description.abstractMOTIVATION: Rapid development in sequencing technologies has dramatically improved our ability to detect genetic variants in human genome. However, current methods have variable sensitivities in detecting different types of genetic variants. One type of such genetic variants that is especially hard to detect is inversions. Analysis of public databases showed that few short inversions have been reported so far. Unlike reads that contain small insertions or deletions, which will be considered through gap alignment, reads carrying short inversions often have poor mapping quality or are unmapped, thus are often not further considered. As a result, the majority of short inversions might have been overlooked and require special algorithms for their detection. RESULTS: Here, we introduce SRinversion, a framework to analyze poorly mapped or unmapped reads by splitting and re-aligning them for the purpose of inversion detection. SRinversion is very sensitive to small inversions and can detect those less than 10 bp in size. We applied SRinversion to both simulated data and high-coverage sequencing data from the 1000 Genomes Project and compared the results with those from Pindel, BreakDancer, DELLY, Gustaf and MID. A better performance of SRinversion was achieved for both datasets for the detection of small inversions.-
dc.languageeng-
dc.publisherOxford University Press. The Journal's web site is located at http://bioinformatics.oxfordjournals.org/-
dc.relation.ispartofBioinformatics-
dc.rightsPre-print: Journal Title] ©: [year] [owner as specified on the article] Published by Oxford University Press [on behalf of xxxxxx]. All rights reserved. Pre-print (Once an article is published, preprint notice should be amended to): This is an electronic version of an article published in [include the complete citation information for the final version of the Article as published in the print edition of the Journal.] Post-print: This is a pre-copy-editing, author-produced PDF of an article accepted for publication in [insert journal title] following peer review. The definitive publisher-authenticated version [insert complete citation information here] is available online at: xxxxxxx [insert URL that the author will receive upon publication here]. -
dc.titleSRinversion: a tool for detecting short inversions by splitting and re-aligning poorly mapped and unmapped sequencing reads-
dc.typeArticle-
dc.identifier.emailLau, YL: lauylung@hku.hk-
dc.identifier.emailYang, W: yangwl@hkucc.hku.hk-
dc.identifier.authorityLau, YL=rp00361-
dc.identifier.authorityYang, W=rp00524-
dc.identifier.doi10.1093/bioinformatics/btw516-
dc.identifier.scopuseid_2-s2.0-85016215595-
dc.identifier.hkuros280952-
dc.identifier.volume32-
dc.identifier.spage3559-
dc.identifier.epage3565-
dc.identifier.isiWOS:000392749500004-
dc.publisher.placeUnited Kingdom-
dc.identifier.issnl1367-4803-

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