Dataset Information

CHRR: coordinate hit-and-run with rounding for uniform sampling of constraint-based models.

ABSTRACT:

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.

SUBMITTER: Haraldsdottir HS

PROVIDER: S-EPMC5447232 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

CHRR: coordinate hit-and-run with rounding for uniform sampling of constraint-based models.

Haraldsdóttir Hulda S HS Cousins Ben B Thiele Ines I Fleming Ronan M T RMT Vempala Santosh S

Bioinformatics (Oxford, England) 20170601 11

<h4>Summary</h4>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-an ...[more]

PMID: 28158334

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Dataset Information

CHRR: coordinate hit-and-run with rounding for uniform sampling of constraint-based models.

Summary

Availability and implementation

Contact

Supplementary information

Publications

CHRR: coordinate hit-and-run with rounding for uniform sampling of constraint-based models.

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