CSA-X: Modularized Constrained Multiple Sequence Alignment

Imposing additional constraints on multiple sequence alignment (MSA) algorithms can often produce more biologically meaningful alignments. Hence, various constrained multiple sequence alignment (CMSA) algorithms have been developed in the literature, where researchers used anchor points, regular expressions, or context-free-grammars to specify the constraints, wherein alignments produced are forced to align around segments that match the constraints. In this thesis, we propose CSA-X, a modularized program of constrained multiple sequence alignment that accepts constraints in the form of regular expressions. It uses an arbitrary underlying multiple sequence alignment program to generate alignments, and is therefore modular. The name CSA-X refers to our proposed program generally, where the letter X is substituted with the name of a (non-constrained) multiple sequence alignment algorithm which is used as underlying MSA engine in the proposed program. We compare the accuracy of our program with another constrained multiple sequence alignment program called RE-MuSiC that similarly uses regular expressions for constraints. In addition, comparisons are also made to the underlying MSA programs (without constraints). The BAliBASE 3.0 benchmark database is used to assess the performance of the proposed program CSA-X, other MSA programs, and CMSA programs considered in this study. Based on the results presented herein, CSA-X outperforms RE-MuSiC, and scores well against the underlying alignment programs. It also shows that the use of regular expression constraints, if chosen well, created from the least conserved region of the correct alignments, improves the alignment accuracy. In this study, ProbCons and T-Coffee are used as the underlying MSA programs in CSA-X, and the accuracy of the alignments are measured in terms of Q score and TC score. On average, CSA-X used with constraints identified from the least conserved regions of the correct alignments achieves results that are 17.65% more for Q score, and 23.7% more for TC score compared to RE-MuSiC. In fact, CSA-X with ProbCons (CSA-PC) achieves a higher score in over 97.9% of the cases for Q score, and over 96.4% of the cases for TC score. In addition, CSA-X with T-Coffee (CSA-TCOF) achieves a higher score in over 97.7% of the cases for Q score, and over 94.8% of the cases for TC score. Furthermore, CSA-X with regular expressions created from the least conserved regions of the correct alignments achieves higher accuracy scores compared to standalone ProbCons and T-Coffee. To measure the statistical significance of CSA-X results, the Wilcoxon rank-sum test and Wilcoxon signed-rank test are performed, and these tests show that CSA-X results for the least conserved regular expression constraint sets from the correct BAliBASE 3.0 alignments are significantly different than those from RE-MuSiC, ProbCons, and T-Coffee.

Name thesis:degree_name

Master of Science (M.Sc.)

Level thesis:degree_level

Masters

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Saskatchewan

Year dc:date.issued

2015

Author dc:creator

• Islam, T M Rezwanul

Advisor dc:contributor.advisor

• McQuillan, Ian

Committee members dc:contributor.committeemember

• Kusalik, Anthony
• Keil, Mark
• Wu, FangXiang

• Multiple Sequence Alignment, Constrained Multiple Sequence Alignment.

Language dc:language.iso

eng

Handle dc:identifier.uri

https://hdl.handle.net/10388/ETD-2015-10-2276

OAI identifier oai:identifier

oai:harvest.usask.ca:10388/ETD-2015-10-2276