hello, i used Biopython and i used the pairwise2.align.localms function of Smith-Waterman alignment. but in the output i have the score of alignment and i need to calculate the e-value of this alignment of improving the efficiency of the alignment. can you help me to calculate the e-value using the score please?
The Smith-Waterman algorithm finds the optimal (i.e. highest scoring) local alignment given a scoring matrix. Local alignment statistics are well understood, see for example NCBI's page on statistics of sequence similarity scores. To roll out your own computation, this post may be useful. Finally, some implementations of the algorithm (e.g. ssearch from the FASTA package) do give an e-value and it may be simpler/easier/faster to use one of these. Note that e-values only make sense in the context of a database search.
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version 2.3.6
thanks for your response. But the e-value have a sense when i compare two sequences.
Yes, you're right, by definition, the e-value applies to a pairwise sequence alignment. However, I don't understand what you mean by ' improving the efficiency of the alignment'. The Smith-Waterman algorithm is guaranteed to find the optimal local alignment. Are you concerned that you may have multiple optimal alignments ? By the way, chapter 4 of the O'Reilly BLAST book by Korf et al. also explains in details how to calculate the e-value.
in alignment of two sequences: if i applicate the SW algorithm, i have an alignment but in other case if the two sequences do not actually align. For this, I want to calculate e-value to determine a threshold if the two sequences align (if I get a good e-value) or not. If not, if you have an idea to determine from the score of the alignment exists or not? because i use pairwise2.align.localms from Biopython Thank you for your reply