Boosting forward-time population genetic simulators through genotype compression.

ABSTRACT:

Background

Forward-time population genetic simulations play a central role in deriving and testing evolutionary hypotheses. Such simulations may be data-intensive, depending on the settings to the various parameters controlling them. In particular, for certain settings, the data footprint may quickly exceed the memory of a single compute node.

Results

We develop a novel and general method for addressing the memory issue inherent in forward-time simulations by compressing and decompressing, in real-time, active and ancestral genotypes, while carefully accounting for the time overhead. We propose a general graph data structure for compressing the genotype space explored during a simulation run, along with efficient algorithms for constructing and updating compressed genotypes

SUBMITTER: Ruths T 

PROVIDER: S-EPMC3700844 | biostudies-literature | 2013 Jun

REPOSITORIES: biostudies-literature