cdanielmachado / reframed

ReFramed: metabolic modeling package
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Transcriptomics usage #26

Open FelipeMelis opened 9 months ago

FelipeMelis commented 9 months ago

Hello,

I'm struggling with the type of data that you require for transcriptomics functions: what is the structure of the dict gene_exp that you need?

def eFlux(model, gene_exp, scale_rxn=None, scale_value=1, constraints=None, parsimonious=False):
    """ Run an E-Flux simulation (Colijn et al, 2009).

    Arguments:
        model (CBModel): model
        gene_exp (dict): transcriptomics data
        scale_rxn (str): reaction to scale flux vector (optional)
        scale_value (float): scaling factor (mandatory if scale_rxn is specified)
        constraints (dict): additional constraints (optional)
        parsimonious (bool): compute a parsimonious solution (default: False)

    Returns:
        Solution: solution
    """
Rohak72 commented 4 months ago

Hi @FelipeMelis,

Did you ever find a solution to this? I'm dealing with the same issue, so it'd be great to get your feedback!

Thanks, Rohak

FelipeMelis commented 4 months ago

Hi! Finally, I used MEWpy implementation. Uses tables with the expression levels.

Rohak72 commented 4 months ago

Hi Felipe,

Yup, planning to do the same! Thank you for the advice :-)

Best, Rohak

cdanielmachado commented 4 months ago

Sorry for the very late reply guys, I struggle to keep up with issue requests... :)

gene_exp is a dictionary where the keys are gene ids (same as in the model) and the values are the gene expression