Estimates the proportion of genes for each individual that originates from specific founder groups (e.g., breeds, source populations).
Value
A data.table with columns:
Ind: Individual ID.One column per tracked label (named after each unique value in
foundervaramong founders, or as specified bytarget_labels). Each value gives the proportion of genes (0–1) originating from that founder group. Row sums across all label columns equal 1.
Examples
# \donttest{
library(data.table)
# Create dummy labels for founders
tp <- tidyped(small_ped)
tp_dated <- copy(tp)
founders <- tp_dated[is.na(Sire) & is.na(Dam), Ind]
# Assign 'LineA' and 'LineB'
tp_dated[Ind %in% founders[1:(length(founders)/2)], Origin := "LineA"]
#> Tidy Pedigree Object
#> Index: <Ind>
#> Ind Sire Dam Family FamilySize Gen Sex IndNum SireNum DamNum
#> <char> <char> <char> <char> <int> <int> <char> <int> <int> <int>
#> 1: A <NA> <NA> <NA> 1 1 male 1 0 0
#> 2: B <NA> <NA> <NA> 1 1 female 2 0 0
#> 3: F <NA> <NA> <NA> 1 1 female 3 0 0
#> 4: I <NA> <NA> <NA> 1 1 female 4 0 0
#> 5: J1 <NA> <NA> <NA> 1 1 female 5 0 0
#> 6: J2 <NA> <NA> <NA> 1 1 male 6 0 0
#> 7: N <NA> <NA> <NA> 1 1 male 7 0 0
#> 8: O <NA> <NA> <NA> 1 1 female 8 0 0
#> 9: R <NA> <NA> <NA> 1 1 male 9 0 0
#> 10: C A B AxB 3 2 female 10 1 2
#> 11: D A B AxB 3 2 <NA> 11 1 2
#> 12: E A B AxB 3 2 male 12 1 2
#> 13: P N O NxO 2 2 <NA> 13 7 8
#> 14: Q N O NxO 2 2 male 14 7 8
#> 15: G E F ExF 2 3 female 15 12 3
#> 16: H E F ExF 2 3 male 16 12 3
#> 17: K J2 C J2xC 3 3 female 17 6 10
#> 18: L J2 C J2xC 3 3 <NA> 18 6 10
#> 19: M J2 C J2xC 3 3 male 19 6 10
#> 20: S Q J1 QxJ1 2 3 <NA> 20 14 5
#> 21: T Q J1 QxJ1 2 3 male 21 14 5
#> 22: U T K TxK 1 4 male 22 21 17
#> 23: V M G MxG 1 4 female 23 19 15
#> 24: W H I HxI 1 4 female 24 16 4
#> 25: X U V UxV 1 5 female 25 22 23
#> 26: Y R W RxW 1 5 <NA> 26 9 24
#> 27: Z1 N X NxX 2 6 <NA> 27 7 25
#> 28: Z2 N X NxX 2 6 <NA> 28 7 25
#> Ind Sire Dam Family FamilySize Gen Sex IndNum SireNum DamNum
#> <char> <char> <char> <char> <int> <int> <char> <int> <int> <int>
#> Origin
#> <char>
#> 1: LineA
#> 2: LineA
#> 3: LineA
#> 4: LineA
#> 5: <NA>
#> 6: <NA>
#> 7: <NA>
#> 8: <NA>
#> 9: <NA>
#> 10: <NA>
#> 11: <NA>
#> 12: <NA>
#> 13: <NA>
#> 14: <NA>
#> 15: <NA>
#> 16: <NA>
#> 17: <NA>
#> 18: <NA>
#> 19: <NA>
#> 20: <NA>
#> 21: <NA>
#> 22: <NA>
#> 23: <NA>
#> 24: <NA>
#> 25: <NA>
#> 26: <NA>
#> 27: <NA>
#> 28: <NA>
#> Origin
#> <char>
tp_dated[is.na(Origin), Origin := "LineB"]
#> Tidy Pedigree Object
#> Index: <Ind>
#> Ind Sire Dam Family FamilySize Gen Sex IndNum SireNum DamNum
#> <char> <char> <char> <char> <int> <int> <char> <int> <int> <int>
#> 1: A <NA> <NA> <NA> 1 1 male 1 0 0
#> 2: B <NA> <NA> <NA> 1 1 female 2 0 0
#> 3: F <NA> <NA> <NA> 1 1 female 3 0 0
#> 4: I <NA> <NA> <NA> 1 1 female 4 0 0
#> 5: J1 <NA> <NA> <NA> 1 1 female 5 0 0
#> 6: J2 <NA> <NA> <NA> 1 1 male 6 0 0
#> 7: N <NA> <NA> <NA> 1 1 male 7 0 0
#> 8: O <NA> <NA> <NA> 1 1 female 8 0 0
#> 9: R <NA> <NA> <NA> 1 1 male 9 0 0
#> 10: C A B AxB 3 2 female 10 1 2
#> 11: D A B AxB 3 2 <NA> 11 1 2
#> 12: E A B AxB 3 2 male 12 1 2
#> 13: P N O NxO 2 2 <NA> 13 7 8
#> 14: Q N O NxO 2 2 male 14 7 8
#> 15: G E F ExF 2 3 female 15 12 3
#> 16: H E F ExF 2 3 male 16 12 3
#> 17: K J2 C J2xC 3 3 female 17 6 10
#> 18: L J2 C J2xC 3 3 <NA> 18 6 10
#> 19: M J2 C J2xC 3 3 male 19 6 10
#> 20: S Q J1 QxJ1 2 3 <NA> 20 14 5
#> 21: T Q J1 QxJ1 2 3 male 21 14 5
#> 22: U T K TxK 1 4 male 22 21 17
#> 23: V M G MxG 1 4 female 23 19 15
#> 24: W H I HxI 1 4 female 24 16 4
#> 25: X U V UxV 1 5 female 25 22 23
#> 26: Y R W RxW 1 5 <NA> 26 9 24
#> 27: Z1 N X NxX 2 6 <NA> 27 7 25
#> 28: Z2 N X NxX 2 6 <NA> 28 7 25
#> Ind Sire Dam Family FamilySize Gen Sex IndNum SireNum DamNum
#> <char> <char> <char> <char> <int> <int> <char> <int> <int> <int>
#> Origin
#> <char>
#> 1: LineA
#> 2: LineA
#> 3: LineA
#> 4: LineA
#> 5: LineB
#> 6: LineB
#> 7: LineB
#> 8: LineB
#> 9: LineB
#> 10: LineB
#> 11: LineB
#> 12: LineB
#> 13: LineB
#> 14: LineB
#> 15: LineB
#> 16: LineB
#> 17: LineB
#> 18: LineB
#> 19: LineB
#> 20: LineB
#> 21: LineB
#> 22: LineB
#> 23: LineB
#> 24: LineB
#> 25: LineB
#> 26: LineB
#> 27: LineB
#> 28: LineB
#> Origin
#> <char>
# Calculate ancestry proportions for all individuals
anc <- pedancestry(tp_dated, foundervar = "Origin")
print(tail(anc))
#> Ind LineA LineB
#> <char> <num> <num>
#> 1: V 0.75 0.25
#> 2: W 1.00 0.00
#> 3: X 0.50 0.50
#> 4: Y 0.50 0.50
#> 5: Z1 0.25 0.75
#> 6: Z2 0.25 0.75
# }