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A Practical Guide to Phylogenetics for Nonexperts

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Published on: February 5, 2014

G-BLASTN: accelerating nucleotide alignment by graphics processors.

Kaiyong Zhao¹, Xiaowen Chu

¹Department of Computer Science, Hong Kong Baptist University, Hong Kong, China and Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Hong Kong, China.

Bioinformatics (Oxford, England)

|January 28, 2014

Summary

We developed G-BLASTN, a GPU-accelerated tool for nucleotide sequence alignment. This new software significantly speeds up BLAST searches, offering a faster alternative for researchers analyzing large genomic datasets.

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Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

The Basic Local Alignment Search Tool (BLAST) is crucial for sequence similarity searching.
Existing BLAST tools face speed limitations with growing sequence databases.
No GPU-accelerated tool was available for nucleotide sequence alignment using BLAST.

Purpose of the Study:

To develop a GPU-accelerated software tool for nucleotide sequence alignment.
To enhance the speed of BLAST searches for nucleotide sequences.
To provide an alternative to existing sequential and multithreaded BLAST implementations.

Main Methods:

Developed G-BLASTN, a GPU-accelerated nucleotide alignment tool.
Based on the widely used NCBI-BLAST software.
Implemented pipeline mode for batch query processing.

Main Results:

G-BLASTN achieves identical results to NCBI-BLAST.
Offers significant speedups: 14.80X in 'megablast' mode vs. sequential NCBI-BLAST.
Provides 7.15X speedup over 4-core multithreaded NCBI-BLAST in 'megablast' mode.
Achieves 4.32X (1-core) and 1.56X (4-core) speedups in 'blastn' mode.
Pipeline mode improves performance by up to 44% for batch queries.
Currently optimized for long database sequences.

Conclusions:

G-BLASTN offers a substantial performance improvement for nucleotide sequence alignment.
The tool provides a viable GPU-accelerated solution for accelerating BLAST searches.
Future work will focus on optimizing performance for short database sequences.