walhoutlab / merge Goto Github PK

Hi!

I am using iMAT++ to create a model based on RNA-seq data, but for some of my treatment models, the algorithm sets the biomass function as inactive.. Is there a way to make this reaction always active in all runs?

Thank you!

kamoors

Hi! me again...

I am now trying to use iMat++ for a completely different model (not iCEL, not Recon), and I'm currently using the CatExp.py stuff to categorize my gene expression data. However, upon using the gaussian curve plotting to obtain the thresholding values, I encounter some weird stuff..
Firstly, I cannot really grasp how to define the expectedStats values, and how exactly they affect the fitting (thus I'm leaving them as in your walkthrough)
Second, when I do trimodal, I get a good R^2 value, but the mu values are not in the correct order (why?) - the mu1 matches the mean of the curve most to the right, mu2 matches the one on the left (which is negative?), and mu3 matches the curve in the middle. Is this normal?

Thus, later on I defined the rare cutoff as mu2, low cutoff as mu3, and high cutoff as mu1 - correct?

{'mu1': 5.631200169345438,
'sigma1': 1.9850268078063493,
'mu2': 2.585393029325549,
'sigma2': 0.20107748436559067,
'mu3': 4.411776037922199,
'sigma3': 1.0847997002620264,
'N1': 2296.8310628226477,
'N3': 1795.7250793209037,
'N2': -50.55614214355137,
'Rsquared': 0.9960556525960251,
'RSS': 15.82686593199582,
'n': 100}

Thanks in advance :)

MATLAB is throwing errors that the function ''boolean'' is undefined, and I could not find it within this repository.

Could you please provide code or explain its purpose?

Thank you in advance!

Hi!

Still working with your iMAT++ extraction algorithm, and a question arose - can I somehow use the MILP values to constrain a 'regular' iCEL1314 model?

I am currently working with a merged worm-bacterium model, and I would need to test different conditions (thus the iMAT++), but I don't know how (or even if) I can use the output of iMAT++ on my merged model.

The output has many more entries in ub and lb (and not exactly double, went from 2230 to 5571), so I'm not sure how to get the reaction-specific constraints..

Thank you in advance!

Hi, me again..

We are using iMAT++'s integrated FVA function, while also using the CS models separately. While doing FVA on those models using COBRA we were puzzled as to how iMAT++ does FVA.

In the FluxVariability() function from COBRA one can set the % of the objective (e.g. biomass), but I don't see anything like that in the parameters.

Could you please clarify?

Thank you!

Karlis

Hi, again!

Another issue popped up that I cannot understand. As always, I try to fix these myself in the functions, but here I am a bit lost with what is happening. Any help will be appreciated!

Error using eval
Unrecognized function or variable 'X'.

Error in MolMass (line 159)
         substance_mass(ei) = eval(substance_char(ei).first);

Error in IMATplusplus (line 423)
        FluxDistribution(strcmp(worm.rxns,{'EXC0051'})) * MolMass(model.metFormulas{strcmp(model.mets,'protein_BAC[e]')})+...

Error in iMAT_Plus (line 73)
    = IMATplusplus(model,epsilon_f,epsilon_r, ExpCateg, modelType);

I could not find anywhere a mention to 'X', so I assume it is some sort of string that is ''created'' within the function. Any ideas?

Hi, again!

I have come back to your workflow, but have a question about integrating count data.

I want to compare multiple CS models using FVA later on (different conditions from the RNA-seq experiment), so my question is do I need to normalize the count data before applying imat++ on it? In your paper you mention that the conditions are being compared, thus I would assume that if I don't normalize beforehand, this comparison will be problematic?

FYI, I would normalize using DESeq2 integrated normalization, as this is the same thing they used for DE analysis.

Thanks again!

kamoors