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AuReMe / metage2metabo

From annotated genomes to metabolic screening in large scale microbiotas
https://metage2metabo.readthedocs.io
GNU Lesser General Public License v3.0
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M2M workflow and mincom #64

Open ggmirandac opened 2 months ago

ggmirandac commented 2 months ago

Hi,

I have been working with m2m to do some microbial community metabolic interaction analysis and I have stumble with and issue. When trying to run the mincom minimal_community.mincom() function of the python API the target the mincom.json is often empty in the fields that are not the producible metabolites.

I am wondering if this is because of the way that the target.sbml file is created (I am using the main_seeds() function of m2m.main).

Otherwise, in the m2m workflow the optional argumen -t can be left empty and the addvalue metabolites are used. Is there a way to do the same with the python API?

Looking forward for your answer.

ArnaudBelcour commented 1 month ago

Hi @ggmirandac,

This could come from several issues. Are the metabolites present in the target.sbml file contained inside the metabolic networks of your organisms? Especially, are there no added or missing characters compared to the metabolite IDs in the sbml file?

For an in-depth exploration of this issue, is it possible that you share the target.sbml and the mincom.json files?

Otherwise, in the m2m workflow the optional argumen -t can be left empty and the addvalue metabolites are used. Is there a way to do the same with the python API?

This behaviour can be achieved with a call to the metacom_analysis function. If you do not specify the targets_file argument of this function, it will compute the addedvalue metabolites and then use them as targets. And if you set target_com_scope to True, it will use the community scope as the targets instead of the addedvalue metabolites.

Best regards, Arnaud Belcour.

ggmirandac commented 1 month ago

Hi, Thanks for the answer, but I manage to go throught by using the terminal command.