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Currently this code works for peptides in 12 -24 AA range. it appears this in enforced for the percentile calculation. Would removing this limitation still allow for the log odd calcualtions?

Hello,

It's not really an issue, but I was wondering if you had any advice for turning SNP data where I know the amino acid change into a peptide or peptides that will work in this model. I assume with the 14-20 AA length requirement that one should try many different peptides for the one gene mutation? So for example AAAXAAAAAAAAA or AAAAAAAXAAA Where you try the mutation out with different amounts of amino acids in front of it and behind it at the different lengths supported? Thanks for any advice!

Hi, a simple yet very elegant model. Thanks for sharing it. I just wonder if you could please elaborate a bit more about the architecture of the model? More specifically, I would like to know what the states are representing here? Is the it a 3-state model? or sFig1a is just a general illustration.
Also, am I right the think that the reason sticking to python2 (and not 3) is that GHMM is currently supported by py2 and not py3?

Hello，@ikizhvatov
I have some questions while using the hmmhc.How can I use it to predict human data? Maybe there's a way to train human data.

Could you answer me? Thanks！

I have a large list of peptides and wondering what is the format if using a csv file as input. I have tried few ways but doesn't work. Is there a template?