sumstat_tajimas_d {coala} R Documentation

## Summary Statistic: Tajima's D

### Description

This statistic calculates Tajima's D from the simulation results when added to a model. Tajima's D primarily measures an deviation of singletons from the neutral expectation of an equilibrium model. Negative values indicate an excess of singletons, while positive values code a depletion of them.

### Usage

```sumstat_tajimas_d(
name = "tajimas_d",
population = "all",
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. `population` The population for which the statistic is calculated. Can also be "all" to calculate it from all populations. `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

On simulation, this returns a vector with the value of Tajima's D for each locus.

### References

Tajima, F. (1989). "Statistical method for testing the neutral mutation hypothesis by DNA polymorphism.". Genetics 123 (3): 585-95.

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_omega()`, `sumstat_seg_sites()`, `sumstat_sfs()`, `sumstat_trees()`

### Examples

```# A neutral model that should yield values close to zero:
model <- coal_model(5, 2) +
feat_mutation(20) +
feat_recombination(10) +
sumstat_tajimas_d("taji_d")
stats <- simulate(model)
print(stats\$taji_d)
```

[Package coala version 0.6.0 Index]