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CUSHAW: a CUDA compatible short read aligner to large genomes based on the Burrows-Wheeler transform
Yongchao Liu1, Bertil Schmidt, Douglas L Maskell
1School of Computer Engineering, Nanyang Technological University, Singapore 639798, Singapore. liuy@uni-mainz.de
Bioinformatics (Oxford, England)
|May 12, 2012
Summary
CUSHAW is a new parallelized short read aligner that uses graphics processing units (GPUs) to speed up the mapping of sequencing data. This tool offers fast alignment quality comparable to leading aligners for genomics research.
Area of Science:
- Genomics
- Bioinformatics
- Computational Biology
Background:
- High-throughput sequencing technologies generate vast amounts of short read data.
- Mapping short reads to reference genomes presents challenges in alignment quality and speed.
Purpose of the Study:
- To develop a fast and accurate short read aligner.
- To leverage parallel computing for improved alignment performance.
Main Methods:
- Developed CUSHAW, a parallelized aligner using Compute Unified Device Architecture (CUDA).
- Employed a quality-aware bounded search with Burrows-Wheeler Transform (BWT) and Ferragina-Manzini index.
- Utilized CUDA-compatible graphics hardware as accelerators.
Main Results:
- CUSHAW achieves significant speedups on GPUs for short read alignment.
- Demonstrates comparable or superior alignment quality for paired-end reads versus Bowtie, BWA, and SOAP2.
- Shows competitive performance in single-nucleotide polymorphism calling.
Conclusions:
- CUSHAW offers an efficient solution for short read alignment challenges.
- GPU acceleration significantly enhances alignment speed and quality.
- The tool is a valuable asset for large-scale genomics data analysis.
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