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draeger-lab / pymCADRE

pymCADRE enables the reconstruction of tissue-specific metabolic models in Python using transcriptomic data and information of the network topology.
GNU General Public License v3.0
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Same Model Generated by Two Different Transcriptomes #4

Open Rohak72 opened 11 months ago

Rohak72 commented 11 months ago

Hi @NantiaL,

I hope you're doing well! I've successfully run pymCADRE on my system, generating models for the infected and un-infected conditions, respectively. However, despite using different ubiquity scores and transcriptomes for each model run, I end up with the same generic model? I've tried implementing pruning but going through each reaction iteratively would take 16-24 hours and I'm not sure if that's worth the time. Is pruning the solution here, or is it an inherent limitation of the software?

Any clarification would be greatly appreciated, thanks!

Best, Rohak

NantiaL commented 11 months ago

Hey Rohak,

did I understand correctly that you ran only the ranking and not the pruning so far? The pruning would actually result in different final models based on the previous ranking of reactions.

So, although the pruning might take a while, it definitely needs to be done. We have though plans on optimizing the performance of the pruning step.

Rohak72 commented 11 months ago

Hi Nantia,

Ah, I see. Given the size of the generalized model, I'm still unsure whether my machine would be able to finish running the pruning step. Do you know of ways to manually reduce/cut down the genes/reactions/metabolites of the model before running the pruning step (beyond the blocked reactions in the generic model)? Thanks!

Best, Rohak

NantiaL commented 11 months ago

Hi Rohak!

based on your research question you could for example remove pathways (and associated reactions) known to be irrelevant at this point.

Best Nantia