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cleave peptide for fusion gene #25
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Hi, I guess you haven't changed the parameters for Arriba? The default in ScanNeo2 is to filter out the ones with less than 2 supporting reads. Also, ScanNeo2 filters out potential neoantigens that are identical with the corresponding wildtype sequence which for fusion genes is essentially the sequence of the first gene. (https://github.com/ylab-hi/ScanNeo2/blob/52a3818ec3189af502f18eba6b6a1a69b9b3a8c3/workflow/scripts/prioritization/effects.py#L298C3-L303C25). It could be that this filters out some of them. But I can't say for sure. But overall the TESLA validated neoantigens are based on SNV/indels so I wouldn't expect to detect those with gene fusion events, although haven't checked that in detail. Thanks for bringing this to my attention |
What I mean is about how to get the peptide from the output of the fusion analysis using arriba. In the nextneopi.
What I ran on your script, when I require to have the 8 amino acids. It gives me only one sequence:
While nextneopi gives me more by changing the whole sequence from left to right one aa
I think what you already implement on this pipeline can be improved by adding this to get more sequence. |
Thats exactly what I'm doing.. it basically scans the position where the breakpoint appears and use this with a sliding window to determine all possible peptides that include the fusion. So I'm surprised it only gives you one. But thanks again. I will look into it. |
I tested on the test dataset of nextneopi (https://github.com/icbi-lab/nextNEOpi). I has a similar session for using the arriba to get the fusion genes. From those fusion genes, it can get the peptides that are possible to be the neoantigens.
There peptides with 8 amino acids:
PTEN - AC063965.1(21548),MED6P1(31892) MFSGGTCm FSGGTCmg SGGTCmgr GGTCmgrc GTCmgrcm TCmgrcmq Cmgrcmqt mgrcmqty grcmqtyp rcmqtypk cmqtypkv mqtypkvq qtypkvqg typkvqgs#Fusion-out-of-frame#high#yes#chr10:87952259#chr10:88016243#11#1#0#.#.
Your peptides with 8 amino acids:
MFSGGTCm
Is there anything wrong related to my test. Or your pipeline is focused on getting only this peptide rather than getting too much peptides sequence to achieve 37/38 active neoantigens on TELSA dataset?
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