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Summarize a population sample of hybrid scores

Source: R/summaries.R
sample_summaries.Rd

Turns the hybrid index (S) and interspecies heterozygosity (H) of a sample of animals, and optionally their genotypes, into the summary statistics that train_clock() learns from. The same function is used for simulated and observed samples, so the two are always comparable.

Usage

sample_summaries(
  S,
  H,
  diag = NULL,
  shared = NULL,
  n_markers = NULL,
  positions = NULL,
  class_settings = NULL
)

Arguments

S, H

Hybrid index and interspecies heterozygosity of each animal, as from hybrid_scores().

diag

Optional genotype matrix (animals x diagnostic markers) counting species-2 alleles, as from orient_genotypes(). Missing values allowed.

shared

Optional genotype matrix (animals x shared loci) of allele counts. Missing values allowed.

n_markers

Optional number of markers genotyped in each animal, as from hybrid_scores().

positions

Optional marker positions matching the columns of diag: a data.frame with chromosome and position. With them, the rate at which each hybrid's genotype switches between neighbouring markers along a chromosome is summarized (switch_rate, switch_rate_sd). Switches are ancestry junctions plus genotyping noise; they accumulate with every generation of recombination (Janzen et al. 2018), so they date early generations even when animals look alike in S and H.

class_settings

Settings of the classes behind the class shares (see class_settings()); the same settings must be used for the reference and the data.

Value

A named numeric vector.

Details

The sample is first oriented so that the rarer species among its hybrids counts as species 2 (S below 0.5). The summaries then describe:

  • the spread of animals over the S-H triangle (means, percentiles, and the share of animals in each cell of a 10 x 6 grid);

  • heterozygosity relative to its maximum for each animal's ancestry (2 * min(S, 1 - S)) and to the minimum possible for unrelated parents (2 * S * (1 - S)). Values below the latter point to inbreeding;

  • with diag, how unevenly the rarer species' alleles are spread across markers (drift);

  • with shared, inbreeding (shared_fis) and excess linkage disequilibrium (shared_ld) at loci that do not differ between species;

  • with n_markers, the share of animals in each class of classify_hybrids() (pure, F1, F2, first and second backcrosses toward the common or the rare species, and later generations).

Examples

set.seed(1)
S <- c(0, 0, 0.12, 0.25, 0.3, 0.06, 0.5)
H <- c(0, 0, 0.22, 0.48, 0.41, 0.12, 1)
round(sample_summaries(S, H)[1:12], 3)
#>         n_hybrids share_pure_common   share_pure_rare            mean_S 
#>             5.000             0.286             0.000             0.176 
#>              sd_S             q10_S             q50_S             q90_S 
#>             0.185             0.000             0.120             0.380 
#>            mean_H              sd_H             q10_H             q50_H 
#>             0.319             0.354             0.000             0.220