sumstat_omega {coala}

Summary Statistic: Omega

Description

Calculates the Omega Statistic introduced by Kim & Nielsen (2004) from the simulated data. The statistic is sensitive for hard selective sweeps. To calculate the statistic, coala relies on the command line program OmegaPlus, which needs to be downloaded and compiled manually in order to use the statistic.

Usage

sumstat_omega(
  name = "omega",
  min_win = 100,
  max_win = 1000,
  grid = 1000,
  binary = "automatic",
  transformation = identity
)

Arguments

name

The name of the summary statistic. When simulating a model, the value of the statistics are written to an entry of the returned list with this name. Summary statistic names must be unique in a model.

min_win

The minimum distance from the grid point that a SNP must have to be included in the calculation of omega.

max_win

The maximum distance from the grid point that a SNP must have to be included in the calculation of omega.

grid

The number of points for which omega is calculated on each locus. Should be significantly lower than the locus length.

binary

The path of the binary for OmegaPlus. If set to "automatic", coala will try to find a binary called "OmegaPlus" using the PATH environment variable.

transformation

An optional function for transforming the results of the statistic. If specified, the results of the transformation are returned instead of the original values.

Value

A data frame listing of locus, genetic position and the calculated omega value.

References

Linkage disequilibrium as a signature of selective sweeps. Y. Kim and R. Nielsen (2004). Genetics, 167, 1513-1524.

OmegaPlus: a scalable tool for rapid detection of selective sweeps in whole-genome datasets. N. Alachiotis, A. Stamatakis and P. Pavlidis (2012). Bioinformatics Vol. 28 no. 17 2012, pages 2274-2275 doi:10.1093/bioinformatics/bts419

See Also

To create a demographic model: coal_model

To calculate this statistic from data: calc_sumstats_from_data

Other summary statistics: sumstat_dna(), sumstat_file(), sumstat_four_gamete(), sumstat_ihh(), sumstat_jsfs(), sumstat_mcmf(), sumstat_nucleotide_div(), sumstat_seg_sites(), sumstat_sfs(), sumstat_tajimas_d(), sumstat_trees()

Examples

## Not run: 
model <- coal_model(20, 1, 50000) +
  feat_recombination(50) +
  feat_mutation(1000) +
  feat_selection(strength_A = 1000, time = 0.03) +
  sumstat_omega()
stats <- simulate(model)
plot(stats$omega$omega, type = "l")
## End(Not run)