Progressive alignment using Shortest Common Supersequence

Multiple Sequence Alignment is an NP-hard problem. The complexity of finding the optimal alignment is O(L^N) where L is the length of the longest sequence and N is the number of sequences. Hence the optimal solution is nearly impossible for most of the datasets. Progressive alignment solves MSA in very economic complexity but does not provide accurate solutions because there is a tradeoff between accuracy and complexity. Guide tree that guides the alignment of sequences is generated by alignment score in progressive alignment. In this paper, Shortest Common Supersequence (SCS) is utilized to generate the guide tree for progressive alignment and the output alignment results are checked by BAliBASE benchmarks for accuracy. According to SP and TC scores, progressive alignment using the guide tree generated by SCS is better than the guide tree generated by alignment score. Original ClustalW2.1 is modified by SCS, and modified ClustalW2.1 gives better results than the original tool.