Literature DB >> 22576173

CUSHAW: a CUDA compatible short read aligner to large genomes based on the Burrows-Wheeler transform.

Yongchao Liu1, Bertil Schmidt, Douglas L Maskell.   

Abstract

MOTIVATION: New high-throughput sequencing technologies have promoted the production of short reads with dramatically low unit cost. The explosive growth of short read datasets poses a challenge to the mapping of short reads to reference genomes, such as the human genome, in terms of alignment quality and execution speed.
RESULTS: We present CUSHAW, a parallelized short read aligner based on the compute unified device architecture (CUDA) parallel programming model. We exploit CUDA-compatible graphics hardware as accelerators to achieve fast speed. Our algorithm uses a quality-aware bounded search approach based on the Burrows-Wheeler transform (BWT) and the Ferragina-Manzini index to reduce the search space and achieve high alignment quality. Performance evaluation, using simulated as well as real short read datasets, reveals that our algorithm running on one or two graphics processing units achieves significant speedups in terms of execution time, while yielding comparable or even better alignment quality for paired-end alignments compared with three popular BWT-based aligners: Bowtie, BWA and SOAP2. CUSHAW also delivers competitive performance in terms of single-nucleotide polymorphism calling for an Escherichia coli test dataset. AVAILABILITY: http://cushaw.sourceforge.net

Entities:  

Mesh:

Year:  2012        PMID: 22576173     DOI: 10.1093/bioinformatics/bts276

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  39 in total

1.  Short Read Mapping: An Algorithmic Tour.

Authors:  Stefan Canzar; Steven L Salzberg
Journal:  Proc IEEE Inst Electr Electron Eng       Date:  2015-09-07       Impact factor: 10.961

2.  SRPRISM (Single Read Paired Read Indel Substitution Minimizer): an efficient aligner for assemblies with explicit guarantees.

Authors:  Aleksandr Morgulis; Richa Agarwala
Journal:  Gigascience       Date:  2020-04-01       Impact factor: 6.524

3.  An overview and metanalysis of machine and deep learning-based CRISPR gRNA design tools.

Authors:  Jun Wang; Xiuqing Zhang; Lixin Cheng; Yonglun Luo
Journal:  RNA Biol       Date:  2019-09-27       Impact factor: 4.652

4.  A Whole Methylome Study of Ethanol Exposure in Brain and Blood: An Exploration of the Utility of Peripheral Blood as Proxy Tissue for Brain in Alcohol Methylation Studies.

Authors:  Shaunna L Clark; Blair N Costin; Robin F Chan; Alexander W Johnson; Linying Xie; Jessica L Jurmain; Gaurav Kumar; Andrey A Shabalin; Ashutosh K Pandey; Karolina A Aberg; Michael F Miles; Edwin van den Oord
Journal:  Alcohol Clin Exp Res       Date:  2018-11-11       Impact factor: 3.455

5.  Review of applications of high-throughput sequencing in personalized medicine: barriers and facilitators of future progress in research and clinical application.

Authors:  Gaye Lightbody; Valeriia Haberland; Fiona Browne; Laura Taggart; Huiru Zheng; Eileen Parkes; Jaine K Blayney
Journal:  Brief Bioinform       Date:  2019-09-27       Impact factor: 11.622

Review 6.  In the spotlight: Bioinformatics.

Authors:  May Dongmei Wang
Journal:  IEEE Rev Biomed Eng       Date:  2012-11-19

7.  SOAP3-dp: fast, accurate and sensitive GPU-based short read aligner.

Authors:  Ruibang Luo; Thomas Wong; Jianqiao Zhu; Chi-Man Liu; Xiaoqian Zhu; Edward Wu; Lap-Kei Lee; Haoxiang Lin; Wenjuan Zhu; David W Cheung; Hing-Fung Ting; Siu-Ming Yiu; Shaoliang Peng; Chang Yu; Yingrui Li; Ruiqiang Li; Tak-Wah Lam
Journal:  PLoS One       Date:  2013-05-31       Impact factor: 3.240

8.  Long read alignment based on maximal exact match seeds.

Authors:  Yongchao Liu; Bertil Schmidt
Journal:  Bioinformatics       Date:  2012-09-15       Impact factor: 6.937

9.  A hybrid short read mapping accelerator.

Authors:  Yupeng Chen; Bertil Schmidt; Douglas L Maskell
Journal:  BMC Bioinformatics       Date:  2013-02-26       Impact factor: 3.169

10.  CUDASW++ 3.0: accelerating Smith-Waterman protein database search by coupling CPU and GPU SIMD instructions.

Authors:  Yongchao Liu; Adrianto Wirawan; Bertil Schmidt
Journal:  BMC Bioinformatics       Date:  2013-04-04       Impact factor: 3.169

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