Comments (7)
hi @bhargava-morampalli , can I ask if you modify some of the codes because I think the script name should be m6anet-run_inference? Anyway it seems that you are passing None type to the os.path.join argument somewhere in the script, is it possible that the problem is because you use -i and -o instead of --input_dir and --output_dir, that's why the command line does not recognize the input and output directory argument?
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Oh, sorry - I just followed the quick start thing. So, I should use run_inference instead of inference?
m6anet-inference -input_dir demo_data --out_dir demo_data ---n_processes 4
I have not touched any code. Also, for inference - --input_dir and --out_dir did not work - that's why I changed them to -i and -o. I will try with run_inference and let you know if it works.
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Okay, I used the m6anet-run_inference and I got the data.result.csv.gz file. It's very small and only a few bytes. Is this normal?
also, n_processes is for allocating the threads - is it correct?
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Ah I see, it's weird that it can still execute m6anet-inference, perhaps I have forgotten to clear some files / cache, let me check that on my end. Apology for the typo in the documentation, I have just updated it so that people will not mistake the command. Thanks!
Anyway, you are right, --n_processes is to allocate the number of threads. Also, by default m6anet will require each position to have at least 20 reads. May I know the size of the data.readcount files (like how many rows and whether they seem to have a lot of positions with at least 20 reads)? Also, can you check if the entries inside data.result.csv.gz make sense?
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That's great, thanks. I will check the data.readcount and also about the data in csv.gz. I will let you know the results.
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oh right, please try out with --input_dir instead of -input_dir as stated in the documentation before, that was a typo that I have corrected in the documentation, again, sorry for this
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hi @bhargava-morampalli , can I ask if you have managed to run this successfully? If you have, then I want to close this issue, otherwise please let me know of any problems you are facing with running m6anet
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Related Issues (20)
- Memory usage exploding HOT 3
- Empty Eventalign.txt for Negative Sense Viral RNA HOT 1
- dataprep and data.log HOT 8
- Questions about the m6A motif HOT 1
- Genome vs transcriptome alignment HOT 4
- m6anet, eventalign, galaxy HOT 3
- error with m6anet dataprep HOT 1
- yet another error with m6anet dataprep HOT 1
- running with test eventalign test file file form github produces another error HOT 8
- installation on linux failed HOT 3
- TypeError: argument should be integer or None, not 'numpy.float64' HOT 2
- Interpreting 'inference' results HOT 1
- m6anet dataprep fails to complete: cannot convert float NaN to integer HOT 3
- Issues with Read Selection HOT 2
- The position output by m6anet seems to be 1 less than the actual position HOT 1
- empty dataprep data.json and data.log HOT 5
- Arabidopsis VIRC instead of col0 (wild type) HOT 3
- probability_modified and mod_ratio are 0 HOT 2
- f5c or nanopolish HOT 3
- Disconnect between site and individual read mod probability RNA004
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