I am working on a transcriptome file and now i need to retrieve only the reads that have ORFs shorter than 100 amino acids and discard the reads which have viable ORFs (more than 100 amino acids). When i used Transdecoder it can retrieve only the reads with ORFs greater than 100 and discard the reads having shorter ORFs. But i have a requirement which is exactly opposite, that is only to retrieve only the non-viable ORFs.
If you know all transcripts that have >100 aa ORFs, you can just remove all of them from your original fasta file (before Transdecoder), which should leave the ones that were not selected by Transdecoder because they have smaller ORFs. I'm not familiar with Transdecoder output but I'm guessing it should work.
I use another program to analyse ORFs in transcripts called Annocript. It also outputs the ORF info for each transcript, from that it's pretty easy to get what you need.
The way I would do it from Annocript output is to filter the output table to keep only the transcripts with get their IDs -> keep only these transcripts in my fasta file (I have a script for it in https://github.com/nat2bee/fasta-manipulation/blob/master/FastaChomper_coding.py).
If you know all transcripts that have >100 aa ORFs, you can just remove all of them from your original fasta file (before Transdecoder), which should leave the ones that were not selected by Transdecoder because they have smaller ORFs. I'm not familiar with Transdecoder output but I'm guessing it should work.
I use another program to analyse ORFs in transcripts called Annocript. It also outputs the ORF info for each transcript, from that it's pretty easy to get what you need.
The way I would do it from Annocript output is to filter the output table to keep only the transcripts with get their IDs -> keep only these transcripts in my fasta file (I have a script for it in https://github.com/nat2bee/fasta-manipulation/blob/master/FastaChomper_coding.py).
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