dingo: a Python package for metabolic flux sampling

Abstract Summary We present dingo , a Python package that supports a variety of methods to sample from the flux space of metabolic models, based on state-of-the-art random walks and rounding methods. For uniform sampling dingo ’s implementation of the Multiphase Monte Carlo Sampling algorithm, provides a significant speed-up and outperforms existing software. Indicatively, dingo can sample from the flux space of the largest metabolic model up to now (Recon3D) in less than 30 hours using a personal computer, under several statistical guarantees; this computation is out of reach for other similar software. In addition, supports common analysis methods, such as Flux Balance Analysis (FBA) and Flux Variability Analysis (FVA), and visualization components. dingo contributes to the arsenal of tools in metabolic modeling by enabling flux sampling in high dimensions (in the order of thousands). Availability and implementation https://github.com/GeomScale/dingo Contact tolis.chal@gmail.gr , haris.zafeiropoulos@kuleuven.be