Frequently asked questions (FAQ)
How are fluxes calculated?
We provide details on the flux calculation approach implemented in PhysioFit in the Method section.
How many measurements should I use to calculate fluxes?
As in any model-based fitting procedure, more data usually means more accurate and precise flux estimates. The minimal number of measurements depend on the model used for flux calculation. For instance, for steady-state built-in models provided with PhysioFit, we recommend using at least 6 to 8 time points, which should provide reliable and meaningful estimates in most situations.
Still, the exact answer to this question strongly depends on the uptake/production/growth rates of your (micro)organism in the conditions you are investigating, on the sampling time interval, on the questions you are addressing, on the model used for flux calculation, and on many other parameters! You can make some tests by calculating fluxes from (published or theoretical) datasets similar to those you have in mind.
Can I calculate fluxes in case of missing values?
Yes, fluxes can still be calculated if some measurement(s) are missing. In this case, let empty the corresponding field of the input data file.
What units should be used for input data?
Input data (biomass concentration, metabolites concentrations, and time) can be provided to PhysioFit using any unit. Still, we recommand to use units for which values are as close to unity as possible to ensure numerical stability (e.g. 3 mM instead of 3.10-3 M). Importantly, units of the estimated fluxes depend on units of time and metabolites and biomass concentrations. The concentration of different metabolites can be provided using different units, but a single unit must be used for all measurements of a given metabolite.
See also
What are the flux units?
Flux units depend on the units of time and concentrations (of biomass and metabolites) provided in the input data file. For instance, if biomass units are in grams of cell dry weight by liter (gCDW/L), metabolite concentrations are in millimolar (mM) and time is in hours (h), the estimated fluxes will be in mmol/gCDW/h. Units should thus be carefully selected, and calculated fluxes must be interpreted consistently with the concentration units.
An error has been raised. What should I do?
The first thing to do is to read the error message which might contain information on how to resolve it. If not, check the FAQ section (yes, this one) to see if the error has been explained in more depth. If the error persists or if you do not understand the error, please post it in the “issues” section on GitHub. We will try to respond as quickly as possible to solve your problem.
What parameters values should I use?
Details on PhysioFit parameters can be found in the Tutorial section.
How can I check if my data have been fitted correctly?
The quality of the fit can be evaluated based on:
the plots of experimental vs simulated data for the best fit, which should be as close as possible,
the χ² statistical test results given in the log file (see below for help on interpreting the results).
What is a χ² test?
A χ² test describes how well a model fits a set of observations. Measures of goodness of fit typically summarize the discrepancy between observed values and the values expected under the model used in PhysioFit (see the Method section). It is calculated as the sum of differences between measured and simulated values, each squared and divided by the simulated value. A good fit corresponds to small differences between measured and simulated values, thereby the χ² value is low. In contrast, a bad fit corresponds to large differences between simulations and measurements, and the χ² value is high.
The resulting χ² value can then be compared with a χ² distribution to determine the goodness of fit. The p-value of one-tail χ² test is calculated by PhysioFit from the best fit and is given in the log file (have a look to the Tutorial section). A p-value close to 0 means poor fitting, and a p-value close to 1 means good fitting (keeping in mind that a p-value very close to 1 can be an evidence that standard deviations might be overestimated). A p-value between 0.95 and 1 means the model fits the data good enough with respect to the standard deviations provided (at a 95% confidence level). PhysioFit provides an explicit meassage stating wether the flux data are satisfactorily fitted or not (at a 95% confidence interval).
My data hasn’t been correctly fitted. Why?
A possible reason to explain a bad fit is that standard deviations on measurements (concentration biomass and metabolites) is under-estimated, thereby making the χ² test too stringent. In this case, plots of measured and fitted data should be in agreement. Reliable estimated of standard deviation on measurements must be provided to PhysioFit (have a look to the Tutorial section to see how to check and adjust this parameter).
Another possible reason to explain a bad fit is that a key asumption of the flux calculation method is not respected. For instance, if you use a steady-state model shipped with PhysioFit, cells might not be strictly in metabolic steady-state, i.e. with constant fluxes during the whole experiment. If this key asumption does not occur (e.g. cells are continuously adapting to their environment and fluxes change over time), PhysioFit will not be able to fit the data satisfactorily. In this case, evaluate wether the deviation is significant or not (e.g. based on the detailed χ² statistics or on the plot of fitted vs measured data), and evaluate the potential biases that would be introduced by interpreting (or not) these flux values.
In rare situations, it may also be because some parameters have to be tweaked to help PhysioFit fitting the measurements, which results in obviously aberrant fits (e.g. with flat time-course profiles for all metabolites). This might happen for instance if some measurements are provided in units far from unity (e.g. 1.10-5 M instead of 10 µM). If this situation happens, we suggest modifying the initial values of fluxes, or changing the units of input data, and re-run the flux calculation. For more info on the run parameters and how they may affect the fitting process, please refer to section Flux calculation parameters.
If you believe the problem is in PhysioFit, we would greatly appreciate if you could open a new issue on our issue tracker.
I cannot start PhysioFit graphical user interface, can you help me?
If you installed PhysioFit following our standard procedure and that you are unable
to start PhysioFit by opening a terminal and typing physiofit, then there is indeed
something wrong. Do not panic, we are here to help!
Please follow this simple procedure:
The first step of the debugging process will be to get a traceback, i.e. a message telling us what is actually going wrong. You should see this message in the terminal you opened.
Read the traceback and try to understand what is going wrong:
If it is related to your system or your Python installation, you will need to ask some help from your local system administrator or your IT department so they could guide you toward a clean installation. Tell them that you wanted “to use the graphical user interface of PhysioFit, a Python 3.6 software” and what you did so far (installation), give them the traceback and a link toward the documentation. They should know what to do.
If you believe the problem is in PhysioFit or that your local system administrator told you so, then you probably have found a bug! We would greatly appreciate if you could open a new issue on our issue tracker.
I have develop a new model, can you include it in PhysioFit distribution?
If you have developed a new flux model, we would be happy to include it in PhysioFit! Open a new issue on our issue tracker, and let’s discuss about your model and how we could include it! :)
I would like a new feature.
We would be glad to improve PhysioFit. Please get in touch with us here so we could discuss your problem.