File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: BALSA: integrated secondary analysis for whole-genome and whole-exome sequencing, accelerated by GPU

TitleBALSA: integrated secondary analysis for whole-genome and whole-exome sequencing, accelerated by GPU
Authors
Issue Date2014
Citation
PeerJ, 2014, v. 2, p. e421 How to Cite?
AbstractThis paper reports an integrated solution, called BALSA, for the secondary analysis of next generation sequencing data; it exploits the computational power of GPU and an intricate memory management to give a fast and accurate analysis. Fromraw reads to variants (including SNPs and Indels), BALSA, using just a single computing node with a commodity GPU board, takes 5.5 h to process 50-fold whole genome sequencing (~750 million 100 bp paired-end reads), or just 25 min for 210-fold whole exome sequencing. BALSA's speed is rooted at its parallel algorithms to effectively exploit a GPU to speed up processes like alignment, realignment and statistical testing. BALSA incorporates a 16-genotype model to support the calling of SNPs and Indels and achieves competitive variant calling accuracy and sensitivity when compared to the ensemble of six popular variant callers. BALSA also supports efficient identification of somatic SNVs and CNVs; experiments showed that BALSA recovers all the previously validated somatic SNVs and CNVs, and it is more sensitive for somatic Indel detection. BALSA outputs variants in VCF format. A pileup-like SNAPSHOT format, while maintaining the same fidelity as BAM in variant calling, enables efficient storage and indexing, and facilitates the App development of downstream analyses. BALSA is available at: http://sourceforge.net/p/balsa. © 2014 Luo et al.
Persistent Identifierhttp://hdl.handle.net/10722/204722
PubMed Central ID

 

DC FieldValueLanguage
dc.contributor.authorLuo, Ren_US
dc.contributor.authorWong, YLen_US
dc.contributor.authorLAW, WCen_US
dc.contributor.authorLee, LKen_US
dc.contributor.authorCheung, CLJen_US
dc.contributor.authorLiu, CMen_US
dc.contributor.authorLam, TWen_US
dc.date.accessioned2014-09-20T00:31:55Z-
dc.date.available2014-09-20T00:31:55Z-
dc.date.issued2014en_US
dc.identifier.citationPeerJ, 2014, v. 2, p. e421en_US
dc.identifier.urihttp://hdl.handle.net/10722/204722-
dc.description.abstractThis paper reports an integrated solution, called BALSA, for the secondary analysis of next generation sequencing data; it exploits the computational power of GPU and an intricate memory management to give a fast and accurate analysis. Fromraw reads to variants (including SNPs and Indels), BALSA, using just a single computing node with a commodity GPU board, takes 5.5 h to process 50-fold whole genome sequencing (~750 million 100 bp paired-end reads), or just 25 min for 210-fold whole exome sequencing. BALSA's speed is rooted at its parallel algorithms to effectively exploit a GPU to speed up processes like alignment, realignment and statistical testing. BALSA incorporates a 16-genotype model to support the calling of SNPs and Indels and achieves competitive variant calling accuracy and sensitivity when compared to the ensemble of six popular variant callers. BALSA also supports efficient identification of somatic SNVs and CNVs; experiments showed that BALSA recovers all the previously validated somatic SNVs and CNVs, and it is more sensitive for somatic Indel detection. BALSA outputs variants in VCF format. A pileup-like SNAPSHOT format, while maintaining the same fidelity as BAM in variant calling, enables efficient storage and indexing, and facilitates the App development of downstream analyses. BALSA is available at: http://sourceforge.net/p/balsa. © 2014 Luo et al.-
dc.languageengen_US
dc.relation.ispartofPeerJen_US
dc.titleBALSA: integrated secondary analysis for whole-genome and whole-exome sequencing, accelerated by GPUen_US
dc.typeArticleen_US
dc.identifier.emailWong, YL: vylwong@hku.hken_US
dc.identifier.emailLee, LK: lklee@cs.hku.hken_US
dc.identifier.emailCheung, CLJ: jeannoc@hku.hken_US
dc.identifier.emailLiu, CM: cmliu@cs.hku.hken_US
dc.identifier.emailLam, TW: hresltk@hkucc.hku.hken_US
dc.identifier.authorityLee, LK=rp00140en_US
dc.identifier.authorityLam, TW=rp00135en_US
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.7717/peerj.421en_US
dc.identifier.pmcidPMC4060040-
dc.identifier.scopuseid_2-s2.0-84903843725-
dc.identifier.hkuros239065en_US
dc.identifier.volume2en_US
dc.identifier.spagee421en_US
dc.identifier.epagee421en_US

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats