Evaluating the Accuracy and Efficiency of Multiple Sequence Alignment Methods. (January 2014)

• Record Type: Journal Article
• Authors: Pervez, Muhammad Tariq; Babar, Masroor Ellahi; Nadeem, Asif; Aslam, Muhammad; Awan, Ali Raza; Aslam, Naeem; Hussain, Tanveer; Naveed, Nasir; Qadri, Salman; Waheed, Usman; Shoaib, Muhammad
• Is Part Of: Evolutionary bioinformatics online. Volume 10(2014)
• Publication Date: 2014-01
• Subjects: Multiple Sequence Alignment Tools -- comparative study of MSA tools -- sum of pairs score -- column score -- evolutionary parameters; Bioinformatics -- Periodicals; Evolutionary computation -- Periodicals; Genetic programming (Computer science) -- Periodicals; Computational Biology; Evolution, Molecular; Bioinformatics; Electronic journals; Periodicals; Fulltext; Internet Resources; Periodicals; Periodicals; 576.8
• DOI: 10.4137/EBO.S19199
• Languages: English
• ISSNs: 1176-9343

Abstract

A comparison of 10 most popular Multiple Sequence Alignment (MSA) tools, namely, MUSCLE, MAFFT(L-INS-i), MAFFT (FFT-NS-2), T-Coffee, ProbCons, SATe, Clustal Omega, Kalign, Multalin, and Dialign-TX is presented. We also focused on the significance of some implementations embedded in algorithm of each tool. Based on 10 simulated trees of different number of taxa generated by R, 400 known alignments and sequence files were constructed using indel-Seq-Gen. A total of 4000 test alignments were generated to study the effect of sequence length, indel size, deletion rate, and insertion rate. Results showed that alignment quality was highly dependent on the number of deletions and insertions in the sequences and that the sequence length and indel size had a weaker effect. Overall, ProbCons was consistently on the top of list of the evaluated MSA tools. SATe, being little less accurate, was 529.10% faster than ProbCons and 236.72% faster than MAFFT(L-INS-i). Among other tools, Kalign and MUSCLE achieved the highest sum of pairs. We also considered BALiBASE benchmark datasets and the results relative to BAliBASE- and indel-Seq-Gen-generated alignments were consistent in the most cases.