ABC for GPAS resource optimization (part 4)

[2019-11-26]

Problem statement:

How much resources do we allocate for within or across populations and individual or pool genotyping to optimize prediction accuracy in genomic prediction and QTL detection power in genome-wide association experiments?

Constraints, variables and constants:

Constrained by a fixed number of sequencing experiments
100 equidistant populations in a square lattice
1,000 individuals per population carrying capacity
10,000 loci
5, 10 or 100 QTL under directional selection defined by a symmetric generalized logistic function with a maximal slope of 0.25 at the median.
0 or 100 background selection loci under directional selection also defined by a symmetric logistic function with maximal slope of -0.25, 0.00, or 0.25.
uniform, uni-directional or bi-directional gradients of resistance allele

The challenge is to account for landscape heterogeneity - affected by population genetic forces and highly dynamic.