Summarize Inbreeding Levels — pedfclass • visPedigree

Classifies individuals into inbreeding levels based on their inbreeding coefficients (F) according to standard or user-defined thresholds.

Usage

pedfclass(ped, breaks = c(0.0625, 0.125, 0.25), labels = NULL)

Arguments

ped: A tidyped object.
breaks: Numeric vector of strictly increasing positive upper bounds for inbreeding classes. Default is c(0.0625, 0.125, 0.25), corresponding approximately to half-sib, avuncular/grandparent, and full-sib/parent-offspring mating thresholds. The class "F = 0" is always kept as a fixed first level. A final open-ended class "F > max(breaks)" is always appended automatically.
labels: Optional character vector of interval labels. If NULL, labels are generated automatically from breaks. When supplied, its length must equal length(breaks), with each element naming the bounded interval (breaks[i-1], breaks[i]]. The open-ended tail class is always auto-generated and cannot be overridden.

Value

A data.table with 3 columns:

FClass: An ordered factor. By default it contains 5 levels: "F = 0", "0 < F <= 0.0625", "0.0625 < F <= 0.125", "0.125 < F <= 0.25", and "F > 0.25". The number of levels equals length(breaks) + 2 (the fixed zero class plus one class per bounded interval plus the open-ended tail).
Count: Integer. Number of individuals in each class.
Percentage: Numeric. Percentage of individuals in each class.

Details

The default thresholds follow common pedigree interpretation rules:

F = 0.0625: approximately the offspring of half-sib mating.
F = 0.125: approximately the offspring of avuncular or grandparent-grandchild mating.
F = 0.25: approximately the offspring of full-sib or parent-offspring mating.

Therefore, assigning F = 0.25 to the class "0.125 < F <= 0.25" is appropriate. If finer reporting is needed, supply custom breaks, for example to separate 0.25, 0.375, or 0.5.

Examples

tp <- tidyped(simple_ped, addnum = TRUE)
pedfclass(tp)
#> Calculating inbreeding coefficients...
#> Key: <FClass>
#>                 FClass Count Percentage
#>                  <ord> <int>      <num>
#> 1:               F = 0    58  98.305085
#> 2:     0 < F <= 0.0625     1   1.694915
#> 3: 0.0625 < F <= 0.125     0   0.000000
#> 4:   0.125 < F <= 0.25     0   0.000000
#> 5:            F > 0.25     0   0.000000

# Finer custom classes (4 breaks, labels auto-generated)
pedfclass(tp, breaks = c(0.03125, 0.0625, 0.125, 0.25))
#> Calculating inbreeding coefficients...
#> Key: <FClass>
#>                   FClass Count Percentage
#>                    <ord> <int>      <num>
#> 1:                 F = 0    58  98.305085
#> 2:      0 < F <= 0.03125     1   1.694915
#> 3: 0.03125 < F <= 0.0625     0   0.000000
#> 4:   0.0625 < F <= 0.125     0   0.000000
#> 5:     0.125 < F <= 0.25     0   0.000000
#> 6:              F > 0.25     0   0.000000

# Custom labels aligned to breaks (3 labels for 3 breaks; tail is auto)
pedfclass(tp, labels = c("Low", "Moderate", "High"))
#> Calculating inbreeding coefficients...
#> Key: <FClass>
#>      FClass Count Percentage
#>       <ord> <int>      <num>
#> 1:    F = 0    58  98.305085
#> 2:      Low     1   1.694915
#> 3: Moderate     0   0.000000
#> 4:     High     0   0.000000
#> 5: F > 0.25     0   0.000000

# \donttest{
tp_inbred <- tidyped(inbred_ped, addnum = TRUE)
pedfclass(tp_inbred)
#> Calculating inbreeding coefficients...
#> Key: <FClass>
#>                 FClass Count Percentage
#>                  <ord> <int>      <num>
#> 1:               F = 0     4   57.14286
#> 2:     0 < F <= 0.0625     0    0.00000
#> 3: 0.0625 < F <= 0.125     0    0.00000
#> 4:   0.125 < F <= 0.25     2   28.57143
#> 5:            F > 0.25     1   14.28571
# }