Abstract
Motivation Efficient resource allocation contributes to an organism’s fitness and improves success in competition. The Resource Balance Analysis (RBA) computational framework enables the analysis of an organism’s growth-optimal configurations in various environments, at genome-scale. The existing RBApy software enables the construction of RBA models on genome-scale and the calculation of medium-specific, growth-optimal cell states, including metabolic fluxes and the abundance of macromolecular machines. However, to address the needs of non-expert users, there is a need for a simple programming API, easy to use and interoperable with other software through convenient formats for models and data.
Results The RBAtools python package enables the convenient use of RBA models and addresses non-expert users.
As a flexible programming interface, it enables the implementation of custom workflows and simplifies the modification of existing genome-scale RBA models and data export to various formats. The features comprise simulation, model fitting, parameter screens, sensitivity analysis, variability analysis, and the construction of Pareto fronts. Models and data are represented as structured tables, in HTML, and common formats for fluxomics and proteomics visualization.
Availability Details about RBA can be found at rba.inrae.fr. RBAtools documentation, installation instructions, and tutorials are available at sysbioinra.github.io/rbatools.
Contact wolfram.liebermeister{at}inrae.fr, anne.goelzer{at}inrae.fr
Competing Interest Statement
The authors have declared no competing interest.