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Table 1 Comparison of population simulation methods

From: SimBA: simulation algorithm to fit extant-population distributions

 

epiSim

HapSim

SIMLD

SimBA

Matches MAF distribution

-

X

X

X

Matches r 2 distribution

-

X

X

X

Number of control parameters

0

0

5

1

Population stratification

-

-

-

X

Simulation time

33

12

<1

5

  1. SimBA matches the MAF and r 2 distributions for each marker, without requiring an exemplar population, and uses only one control parameter (k). Time (seconds) is the average time required for one run of the experiment shown in Figure 5(b-e). Experiments were conducted on the same x86_64 Linux Fedora system with 4-core 2.9 GHz processor and 16 GB RAM, except epiSim (requiring Matlab access) on a 64-bit Windows 7 system with 8-core 2.4 GHz processor and 8 GB RAM.
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BMC Bioinformatics

ISSN: 1471-2105

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