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Article: FaSD-somatic: A fast and accurate somatic SNV detection algorithm for cancer genome sequencing data

TitleFaSD-somatic: A fast and accurate somatic SNV detection algorithm for cancer genome sequencing data
Authors
Issue Date2014
Citation
Bioinformatics, 2014, v. 30, n. 17, p. 2498-2500 How to Cite?
AbstractSummary: Recent advances in high-throughput sequencing technologies have enabled us to sequence large number of cancer samples to reveal novel insights into oncogenetic mechanisms. However, the presence of intratumoral heterogeneity, normal cell contamination and insufficient sequencing depth, together pose a challenge for detecting somatic mutations. Here we propose a fast and an accurate somatic single-nucleotide variations (SNVs) detection program, FaSD-somatic. The performance of FaSD-somatic is extensively assessed on various types of cancer against several state-of-the-Art somatic SNV detection programs. Benchmarked by somatic SNVs from either existing databases or de novo higher-depth sequencing data, FaSD-somatic has the best overall performance. Furthermore, FaSD-somatic is efficient, it finishes somatic SNV calling within 14 h on 50X whole genome sequencing data in paired samples. © The Author 2014. Published by Oxford University Press. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/198460
ISSN
2015 Impact Factor: 5.766
2015 SCImago Journal Rankings: 4.643
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorWANG, Wen_US
dc.contributor.authorWANG, Pen_US
dc.contributor.authorXU, Fen_US
dc.contributor.authorLUO, Ren_US
dc.contributor.authorWong, MPen_US
dc.contributor.authorLam, TWen_US
dc.contributor.authorWang, JJen_US
dc.date.accessioned2014-07-07T07:00:31Z-
dc.date.available2014-07-07T07:00:31Z-
dc.date.issued2014en_US
dc.identifier.citationBioinformatics, 2014, v. 30, n. 17, p. 2498-2500en_US
dc.identifier.issn1367-4803-
dc.identifier.urihttp://hdl.handle.net/10722/198460-
dc.description.abstractSummary: Recent advances in high-throughput sequencing technologies have enabled us to sequence large number of cancer samples to reveal novel insights into oncogenetic mechanisms. However, the presence of intratumoral heterogeneity, normal cell contamination and insufficient sequencing depth, together pose a challenge for detecting somatic mutations. Here we propose a fast and an accurate somatic single-nucleotide variations (SNVs) detection program, FaSD-somatic. The performance of FaSD-somatic is extensively assessed on various types of cancer against several state-of-the-Art somatic SNV detection programs. Benchmarked by somatic SNVs from either existing databases or de novo higher-depth sequencing data, FaSD-somatic has the best overall performance. Furthermore, FaSD-somatic is efficient, it finishes somatic SNV calling within 14 h on 50X whole genome sequencing data in paired samples. © The Author 2014. Published by Oxford University Press. All rights reserved.-
dc.languageengen_US
dc.relation.ispartofBioinformaticsen_US
dc.titleFaSD-somatic: A fast and accurate somatic SNV detection algorithm for cancer genome sequencing dataen_US
dc.typeArticleen_US
dc.identifier.emailWong, MP: mwpik@hku.hken_US
dc.identifier.emailLam, TW: hresltk@hkucc.hku.hken_US
dc.identifier.emailWang, JJ: junwen@hku.hken_US
dc.identifier.authorityWong, MP=rp00348en_US
dc.identifier.authorityLam, TW=rp00135en_US
dc.identifier.authorityWang, JJ=rp00280en_US
dc.identifier.doi10.1093/bioinformatics/btu338en_US
dc.identifier.pmid24833803-
dc.identifier.scopuseid_2-s2.0-84907027434-
dc.identifier.hkuros229945en_US
dc.identifier.isiWOS:000342912400057-

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