scoring of alignment of non biological sequence

[huda]

hi,

 

 

 

is the score of sequence alignmnet can be negative when alignmnet non biological sequence?

 

 

 

Note: whether global or local alignmnet

 

 

thanks in advance

[ecoli]

it depends completely on what alignment algorithm and scoring function you use. For ex - if you assign a negative penalty for a mismatch and you have more mismatches than matches you could get a negative score. This is true for any sequence, biological or otherwise.

[huda]

it depends completely on what alignment algorithm and scoring function you use. For ex - if you assign a negative penalty for a mismatch and you have more mismatches than matches you could get a negative score. This is true for any sequence, biological or otherwise.

 

 

thanks, how can asssign value for match, mismatch, gap

sometime gap is given -1, and other time 0, or -2

 

the same thing for match , sometime is given 2 and i other time 1.

 

how can know the best?

 

it depends completely on what alignment algorithm and scoring function you use. For ex - if you assign a negative penalty for a mismatch and you have more mismatches than matches you could get a negative score. This is true for any sequence, biological or otherwise.

 

 

 

 

when I did sequence alignment, I skipped the comparison the element with itself, so get zeros in diagonal. Is the processing is right?

 

which the best method to do clustering given similarity matrix of sequence alignment?

 

and if similarity matrix has zeros in diagonal , is that has affecting the clustering results?

[huda]

it depends completely on what alignment algorithm and scoring function you use. For ex - if you assign a negative penalty for a mismatch and you have more mismatches than matches you could get a negative score. This is true for any sequence, biological or otherwise.

 

Regarding smith_waterman algorithm(local alignment),the main difference to the Needleman–Wunsch algorithm is that negative scoring matrix cells are set to zero, which renders the (thus positively scoring) local alignments visible