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NaN values for (alpha) chain recombination probabilities! #28
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Hi Jonas, For your alpha chains: in general the most problematic step is to get correct gene alignments in the pre processing step, after that the inference/evaluation is pretty smooth. What I would encourage you to do is :
As I mentioned the best results are obtained by constraining the offsets as much as you can provided the sequencing mechanism (having a primer in the V makes you sure of the V offset for instance, as for CDR3s the gene anchors position automatically gives you an offset) and incorrect parameters there may bias your results. I know setting them correctly may seem tedious, but I know by experience that making blind alignments does not work well especially on short sequences (such as CDR3s) |
Hi Quentin, thanks for your detailed answer! Indeed the inference_logs.txt file showed the problem having zeroes. In my case already resetting the threshold for the alignment solved the problem. Cheers, |
Hello, I am adding to this question because I think the problems I am encountering are related, but I am not sure what additional steps to try to resolve nan generation probability for ~10% of mouse CDR3beta sequences (60 bp-long reads) using the built-in models. For a handful of sequences in the Pgen_counts.csv that had nan for Pgen_estimate, I tried the following:
I have not tried using the --ntCDR3 flag in the alignment step because it seems like the alignment step is successful. Should I try using the --ntCDR3 flag? We have indices of V and J positions in the read but it may just take me some thinking to match that to offsets. Thank you! |
Dear @spritelysauropods , As for your other questions:
In general I would advise you to use your V and J position knowledge, especially since you have such short reads (60bp). Disregarding this information is increasing uncertainty for the algorithm and can only produce worse results. |
Hi Quentin,
I noticed that for calculating alpha chain probabilities I have the problem of almost always getting nan-values in the output. I looked at the sequences but I do not see a pattern. At the same time nan-values are an exception for my beta-chains.
Do you have an idea about what is going wrong there?
Best,
Jonas
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