General Information
| Description | Coordinate hit-and-run with rounding for uniform sampling of constraint-based models |
| Homepage | https://github.com/opencobra/cobratoolbox |
Publications
CHRR: coordinate hit-and-run with rounding for uniform sampling of constraint-based models
Summary:
In constraint-based metabolic modelling, physical and biochemical constraints define a polyhedral convex set of feasible flux vectors. Uniform sampling of this set provides an unbiased characterization of the metabolic capabilities of a biochemical network. However, reliable uniform sampling of genome-scale biochemical networks is challenging due to their high dimensionality and inherent anisotropy. Here, we present an implementation of a new sampling algorithm, coordinate hit-and-run with rounding (CHRR). This algorithm is based on the provably efficient hit-and-run random walk and crucially uses a preprocessing step to round the anisotropic flux set. CHRR provably converges to a uniform stationary sampling distribution. We apply it to metabolic networks of increasing dimensionality. We show that it converges several times faster than a popular artificial centering hit-and-run algorithm, enabling reliable and tractable sampling of genome-scale biochemical networks.
Availability and Implementation:
https://github.com/opencobra/cobratoolbox.
Contact:
ronan.mt.fleming@gmail.com or vempala@cc.gatech.edu
Supplementary information:
Supplementary data are available at Bioinformatics online.
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