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- Publisher Website: 10.7717/peerj.421
- Scopus: eid_2-s2.0-84903843725
- WOS: WOS:000347609000003
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Article: BALSA: integrated secondary analysis for whole-genome and whole-exome sequencing, accelerated by GPU
Title | BALSA: integrated secondary analysis for whole-genome and whole-exome sequencing, accelerated by GPU |
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Authors | |
Keywords | Genomics GPU HPC NGS Secondary analysis Variant calling Whole-exome sequencing Whole-genome seqeuncing |
Issue Date | 2014 |
Citation | PeerJ, 2014, v. 2, p. e421 How to Cite? |
Abstract | This 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 Identifier | http://hdl.handle.net/10722/204722 |
PubMed Central ID | |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Luo, R | en_US |
dc.contributor.author | Wong, YL | en_US |
dc.contributor.author | LAW, WC | en_US |
dc.contributor.author | Lee, LK | en_US |
dc.contributor.author | Cheung, CLJ | en_US |
dc.contributor.author | Liu, CM | en_US |
dc.contributor.author | Lam, TW | en_US |
dc.date.accessioned | 2014-09-20T00:31:55Z | - |
dc.date.available | 2014-09-20T00:31:55Z | - |
dc.date.issued | 2014 | en_US |
dc.identifier.citation | PeerJ, 2014, v. 2, p. e421 | en_US |
dc.identifier.uri | http://hdl.handle.net/10722/204722 | - |
dc.description.abstract | This 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.language | eng | en_US |
dc.relation.ispartof | PeerJ | en_US |
dc.subject | Genomics | - |
dc.subject | GPU | - |
dc.subject | HPC | - |
dc.subject | NGS | - |
dc.subject | Secondary analysis | - |
dc.subject | Variant calling | - |
dc.subject | Whole-exome sequencing | - |
dc.subject | Whole-genome seqeuncing | - |
dc.title | BALSA: integrated secondary analysis for whole-genome and whole-exome sequencing, accelerated by GPU | en_US |
dc.type | Article | en_US |
dc.identifier.email | Wong, YL: vylwong@hku.hk | en_US |
dc.identifier.email | Lee, LK: lklee@cs.hku.hk | en_US |
dc.identifier.email | Cheung, CLJ: jeannoc@hku.hk | en_US |
dc.identifier.email | Liu, CM: cmliu@cs.hku.hk | en_US |
dc.identifier.email | Lam, TW: hresltk@hkucc.hku.hk | en_US |
dc.identifier.authority | Lee, LK=rp00140 | en_US |
dc.identifier.authority | Lam, TW=rp00135 | en_US |
dc.description.nature | link_to_OA_fulltext | - |
dc.identifier.doi | 10.7717/peerj.421 | en_US |
dc.identifier.pmcid | PMC4060040 | - |
dc.identifier.scopus | eid_2-s2.0-84903843725 | - |
dc.identifier.hkuros | 239065 | en_US |
dc.identifier.volume | 2 | en_US |
dc.identifier.spage | e421 | en_US |
dc.identifier.epage | e421 | en_US |
dc.identifier.eissn | 2167-8359 | - |
dc.identifier.isi | WOS:000347609000003 | - |
dc.identifier.issnl | 2167-8359 | - |