I want to calculate the exact number of amino acid variation in my sequence data, but I don't know which software could be better choice, did anyone can recommend one to me ? Thanks in advance.
The Variant Effect Predictor tool which appears as an option when you click on Manage your Data allows you to upload a set of variation data and predict the effect of the variants.PolyPhen (=Polymorphism Phenotyping) is an automatic tool for prediction of possible impact of an amino acid substitution on the structure and function of a human protein. This prediction is based on straightforward empirical rules which are applied to the sequence, phylogenetic and structural information characterizing the substitution.
Perhaps you should rephrase the question. It is not entirely clear what you are asking.
If you want to know how many differences from some reference set, there are several consideration: 1) what is the reference set (which transcripts do you consider representative of what you are interested in, i.e., RefSeq, some validated subset, all possible predicted transcripts, etc.); and 2) what prediction software you are going to rely on. For a broader discussion see: http://genomemedicine.com/content/6/3/26
http://genomemedicine.com/content/6/3/26
As Gerard Tromp has pointed out there are several aspects to consider and the paper has some details on that.
As far as some concrete advice goes, I don't think there is a single solution that is right for all cases. Generally I would be quite careful about the transcripts included in the reference. Being too liberal can add a lot of spurious results. How strict you want to be and what the best strategy for filtering transcripts is depends on what exactly you are trying to do. Can you give a bit more detail?
Would this be the same as the edit distance from the reference sequence?
There's a lot of software out there for variant detection, and as people have said above you need to consider what reference data you are going to compare with. Your sequences will all need to be aligned to the same reference (or you can align them together as a multiple alignment and compare to the consensus sequence).
If it's next-generation sequencing data, you could try aligning using BWA than variant detection using GATK.
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