Pairwise sequence alignment algorithms

As a key algorithm in bioinformatics, sequence alignment algorithm is widely used in sequence similarity analysis and genome sequence database search. Existing research focuses mainly on the specific steps of the algorithm or is for specific problems, lack of high-level abstract domain algorithm framework. Multiple sequence alignment algorithms are more complex, redundant, and difficult to understand, and it is not easy for users to select the appropriate algorithm; some computing errors may occur. Based on our constructed pairwise sequence alignment algorithm component library and the convenient software platform PAR, a few expansion domain components are developed for multiple sequence alignment application domain, and specific multiple sequence alignment algorithm can be designed, and its corresponding program, i.e., C++/Java/Python program, can be generated efficiently and thus enables the improvement of the development efficiency of complex algorithms, as well as accuracy of sequence alignment calculation. A star alignment algorithm is designed and generated to demonstrate the development process.

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Improvements on bicriteria pairwise sequence alignment: algorithms and applications

Bioinformatics ◽

10.1093/bioinformatics/btt098 ◽

2013 ◽

Vol 29 (8) ◽

pp. 996-1003 ◽

Cited By ~ 7

Author(s):

M. Abbasi ◽

L. Paquete ◽

A. Liefooghe ◽

M. Pinheiro ◽

P. Matias

Keyword(s):

Sequence Alignment ◽

Pairwise Sequence Alignment ◽

Alignment Algorithms

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GASAL2: a GPU accelerated sequence alignment library for high-throughput NGS data

BMC Bioinformatics ◽

10.1186/s12859-019-3086-9 ◽

2019 ◽

Vol 20 (1) ◽

Cited By ~ 5

Author(s):

Nauman Ahmed ◽

Jonathan Lévy ◽

Shanshan Ren ◽

Hamid Mushtaq ◽

Koen Bertels ◽

...

Keyword(s):

Sequence Alignment ◽

High Throughput ◽

High Performance ◽

Local Alignment ◽

Global Alignment ◽

Pairwise Sequence Alignment ◽

Rna Sequences ◽

Dna And Rna ◽

Alignment Algorithms ◽

Ngs Data

Abstract Background Due the computational complexity of sequence alignment algorithms, various accelerated solutions have been proposed to speedup this analysis. NVBIO is the only available GPU library that accelerates sequence alignment of high-throughput NGS data, but has limited performance. In this article we present GASAL2, a GPU library for aligning DNA and RNA sequences that outperforms existing CPU and GPU libraries. Results The GASAL2 library provides specialized, accelerated kernels for local, global and all types of semi-global alignment. Pairwise sequence alignment can be performed with and without traceback. GASAL2 outperforms the fastest CPU-optimized SIMD implementations such as SeqAn and Parasail, as well as NVIDIA’s own GPU-based library known as NVBIO. GASAL2 is unique in performing sequence packing on GPU, which is up to 750x faster than NVBIO. Overall on Geforce GTX 1080 Ti GPU, GASAL2 is up to 21x faster than Parasail on a dual socket hyper-threaded Intel Xeon system with 28 cores and up to 13x faster than NVBIO with a query length of up to 300 bases and 100 bases, respectively. GASAL2 alignment functions are asynchronous/non-blocking and allow full overlap of CPU and GPU execution. The paper shows how to use GASAL2 to accelerate BWA-MEM, speeding up the local alignment by 20x, which gives an overall application speedup of 1.3x vs. CPU with up to 12 threads. Conclusions The library provides high performance APIs for local, global and semi-global alignment that can be easily integrated into various bioinformatics tools.

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