A comparison of four pair-wise sequence alignment methods

Nadia Essoussi,Sondes Fayech

doi:10.6026/97320630002166

Abstract

Protein sequence alignment has become an essential task in modern molecular biology research. A number of alignment techniques have been documented in literature and their corresponding tools are made available as freeware and commercial software. The choice and use of these tools for sequence alignment through the complete interpretation of alignment results is often considered non-trivial by end-users with limited skill in Bioinformatics algorithm development. Here, we discuss the comparison of sequence alignment techniques based on dynamic programming (N-W, S-W) and heuristics (LFASTA, BL2SEQ) for four sets of sequence data towards an educational purpose. The analysis suggests that heuristics based methods are faster than dynamic programming methods in alignment speed.

Highlights

Protein sequence alignment is an important step in understanding molecular functions from sequences
We discuss the comparison of sequence alignment techniques based on dynamic programming (N-W, Smith & Waterman (S-W)) and heuristics (LFASTA, BL2SEQ) for four sets of sequence data towards an educational purpose
The analysis suggests that heuristics based methods are faster than dynamic programming methods in alignment speed

Summary

Background

Protein sequence alignment is an important step in understanding molecular functions from sequences. Use we execution time as a parameter to compare sequence alignment tools using scoring matrices such as BLOSUM 45, BLOSUM 62 and BLOSUM 80 [5, 6] This comparison is of help to biologist who are non-expert in Bioinformatics to select appropriate sequence tools for specific tasks based on the available in-house infra-structural facilities. Data statistics The distribution of sequences with varying lengths for datasets #1 to #4 is summarized in Table 1 (supplementary material) Sequence comparison such as DS-R DS-20, DS-40 and DS-90 using N-W, S-W, We performed pair-wise alignment for randomly selected LFASTA and BL2SEQ in a one-to-many alignment manner. LFASTA is downloaded from FASTA website (http://faculty.virginia.edu/wrpearson/fasta/win32_fasta/) and BL2SEQ is downloaded from BLAST website (http://www.ncbi.nlm.nih.gov/BLAST/download.shtml)

Discussion

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Conclusion