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Substitution Rate Calculation From Protein Alignment

Hi to all I have blast output for many sequences with only one aligment in the output (blast-options numalignments 1 numdescriptions 1) done with Paramecium protein database. I want to count the substitution for all amino acids with respect to query sequence. ie.How many times Gly replaced by Val in subject, etc. From this output/data I want to calculate log-odds score for protein substitution levels between these 2 species. Are tools available to do this or make such things easier or I have to write (perl-which I know) scripts.

Anybody wants to improve the question for clarity or accuracy feel free to do it!

There is one tool that does something like that but not exactly http://www.ncbi.nlm.nih.gov/pubmed/12854978 MatGAT: an application that generates similarity/identity matrices using protein or DNA sequences.

thank you raghul

scoring alignment

1 answer

I would be concerned using BLAST to generate this information as the same region can be found in multiple HSP/MSP's. Moreover you will lose a lot in information just taking the top HSP. I would use BLAST to gather the sequences you are interested in and use a program such as muscle or probcons to generate the alignment.

The prophecy program from EMBOSS can create a matrix from which that you can calculate this information but would still need some parsing in a scripting language of you choice.

I want to calculate the substitution rate between 2 closely related species only. For eg,I have translated protein sequences (partial & full CDS) from transcriptome of Tetrahymena malaccensis.So I want to calculate the substitution rate of amino acids between Tetrahymena malaccensis & Tetrahymena thermophila to notice amino acid changes that could have contributed to the thermophilic lifestyle of T.thermophila. Hope my explanation is ok thank for the reply raghul

Above still applies: just use blast to get the orthologs.

ok thanks. Can you reference a publication that explains clearly (to an extent), so I can learn better.

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