Question: Calculating the number of synonymous and non-synonymous sites for genes
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gravatar for chlamystar
2.1 years ago by
chlamystar0
chlamystar0 wrote:

Hi all,

I have a list of the numbers of synonymous and non-synonymous SNPs for a large set of genes (please note - do not have the actual SNP sequences just the amounts).

I would like to now calculate the ka/ks ratio however to do so I need to calculate the numbers of synonymous and non synonymous sites in each gene. I can find a lot of information on how to calculate the ka/ks ratio but not for how to get how many sites have the potential to host either synonymous or non-synonymous substitutions.

Any advice how to do so? Especially bearing in mind I am not great at programming - I can run R but do not have access at the moment to things like matlab.

Thanks in advance for any feedback - am a first time user so happy to give more info. Daisy

kaks snp synonymous • 1.3k views
ADD COMMENTlink modified 2.1 years ago by Petr Ponomarenko2.6k • written 2.1 years ago by chlamystar0
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gravatar for Petr Ponomarenko
2.1 years ago by
United States / Los Angeles / ALAPY.com
Petr Ponomarenko2.6k wrote:

Unless you are certain about gene sequences and need very precise data, there is a workaround: assume that ratio of synonymous sites to nonsynonymous per a genomic region, say of 1000 nucleotides, is constant, then Ka/Ks is approximately your synonymous/nonsynonymous SNP data multiplied by that constant. That constant is the same between genes in first approximation and you can rank genes using synonymous/nonsynonymous SNP as if it is Ka/Ks. Now you need to "normalize" by looking at genes you have a neutral selection for sure. Instead of normalization you can test if ratio for a particular gene or set of genes is different from that "norm" that corresponds to neutral selection using chi-squared test or similar statistic. Data might need to be filtered a bit to remove outliers. This is simplified aproach, but other more precise approaches can be used too.

ADD COMMENTlink modified 2.1 years ago • written 2.1 years ago by Petr Ponomarenko2.6k
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