Details

Autor(en) / Beteiligte

• Haraldsdóttir, Hulda S
• Cousins, Ben
• Thiele, Ines
• Fleming, Ronan M T
• Vempala, Santosh
• Wren, Jonathan

Titel

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

Ist Teil von

• Bioinformatics (Oxford, England), 2017-06, Vol.33 (11), p.1741-1743

Ort / Verlag

England: Oxford University Press

Erscheinungsjahr

2017

Quelle

MEDLINE

Beschreibungen/Notizen

• 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. https://github.com/opencobra/cobratoolbox . ronan.mt.fleming@gmail.com or vempala@cc.gatech.edu. Supplementary data are available at Bioinformatics online.