MANGO: a new approach to multiple sequence alignment.
Multiple sequence alignment is a classical and challenging task for biological sequence analysis. The problem is NP-hard. The full dynamic programming takes too much time. The progressive alignment heuristics adopted by most state of the art multiple sequence alignment programs suffer from the 'once a gap, always a gap' phenomenon. Is there a radically new way to do multiple sequence alignment? This paper introduces a novel and orthogonal multiple sequence alignment method, using multiple optimized spaced seeds and new algorithms to handle these seeds efficiently. Our new algorithm processes information of all sequences as a whole, avoiding problems caused by the popular progressive approaches. Because the optimized spaced seeds are provably significantly more sensitive than the consecutive k-mers, the new approach promises to be more accurate and reliable. To validate our new approach, we have implemented MANGO: Multiple Alignment with N Gapped Oligos. Experiments were carried out on large 16S RNA benchmarks showing that MANGO compares favorably, in both accuracy and speed, against state-of-art multiple sequence alignment methods, including ClustalW 1.83, MUSCLE 3.6, MAFFT 5.861, Prob-ConsRNA 1.11, Dialign 2.2.1, DIALIGN-T 0.2.1, T-Coffee 4.85, POA 2.0 and Kalign 2.0.
Zhang
Zefeng
Z
Computational Biology Research Group, Division of Intelligent Software Systems, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China. zhangzf@ict.ac.cn
Lin
Hao
H
Li
Ming
M
D000465:Algorithms; D001483:Base Sequence; D017124:Conserved Sequence / Q000235:genetics; D008969:Molecular Sequence Data; D012313:RNA / Q000737:chemistry* / Q000235:genetics*; D016415:Sequence Alignment / Q000379:methods*; D017423:Sequence Analysis, RNA / Q000379:methods*; D012689:Sequence Homology, Nucleic Acid; D012984:Software
D012313:RNA