Calculate assignment probabilities

For each assigned offspring-parent pair, calculate the probability they are parent-offspring vs otherwise related. Probabilities are scaled to sum to one across all possible* relationships between the pair or trio; see Details.

Usage

CalcParentProbs(Pedigree = NULL, GenoM = NULL, quiet = FALSE, nCores = 1, ...)

Arguments

Pedigree: dataframe with columns id-dam-sire. By default, any non-genotyped individuals are 'dummified'; use Module='par' to ignore them.
GenoM: numeric matrix with genotype data: One row per individual, one column per SNP, coded as 0, 1, 2, missing values as a negative number or NA. You can reformat data with GenoConvert, or use other packages to get it into a genlight object and then use as.matrix.
quiet: logical, suppress messages. No progress is printed when >1 core is used.
nCores: number of computer cores to use. If 2 or 4, package parallel is used (other values are not applicable).
...: Additional arguments passed to CalcPairLL, such as the genotyping error rate Err, age information in LifeHistData and AgePrior, or InclDup to include the probability that the two samples are duplicates.

Value

the Pedigree dataframe with the three applicable columns renamed to id-dam-sire, and 7 additional columns:

Probdam: Probability that individual in dam column is the maternal parent, rather than otherwise related (LL(PO)/sum(LL))
Probsire: Analogous for sire
Probpair: Probability for id-dam-sire trio. Approximated as the minimum of dam conditional on sire and sire conditional on dam, thus not including e.g. both being siblings (those other configurations are considered by sequoia during pedigree reconstruction, but can (currently) not be accessed directly)
dam_alt, sire_alt: Most likely alternative (not PO) relationship between id-dam and id-sire, respectively
Probdam_alt, Probsire_alt: Probability of most likely alternative relationship

Details

The returned probabilities are calculated from the likelihoods used throughout the rest of this package, by scaling them to sum to one across all possible relationships. For Complex='simp' these are PO=parent-offspring, FS=full siblings, HS=half siblings, GP=grand-parental, FA=full avuncular, HA=third degree relatives (incl half avuncular), and U=unrelated. For Complex='full' there are numerous double relationship considered (PO & HS, HS & HA, etc), making both numerator and denominator in the scaling step less unambiguous, and the returned probabilities an approximation.

The likelihoods are calculated by calling CalcPairLL once or twice for each id-dam and id-sire pair: once not conditioning on the co-parent, and once conditional on the co-parent, if any. For genotyped individuals this is done with focal='PO', and for dummy individuals with focal='GP'.

For relationships between a genotyped and a dummy individual, it may only be possible to determine that the genotyped individual is a second degree relative (GP, HS, or FA) to the dummy's offspring. This then results in a probability of at most 0.33, even when the two are indeed parent and offspring.

See CalcPairLL and the vignettes for further details.

Note that for large pedigrees this function can be fairly slow, especially when using CalcPairLL's default Module='ped' and Complex='full'.

Subsetting the genotype data may give different results, as the likelihoods and thus the probabilities depend on the allele frequencies in the sample.

Examples

test_ped <- Ped_griffin[21:25,]
# add an incorrect sire to illustrate
test_ped$sire <- as.character(test_ped$sire)
test_ped$sire[5] <- 'i057_2003_M'
Ped_with_probs <- CalcParentProbs(test_ped, Geno_griffin)
#> ! `GenoM` and `Pedigree` share few common individuals
#>  
#> ℹ Calculating LL for  dam_solo
#> ℹ Conditioning on pedigree with 145 individuals, 5 dams and 4 sires
#> Transferring input pedigree ...
#>  
#> ℹ Calculating LL for  sire_solo
#> ℹ Conditioning on pedigree with 145 individuals, 5 dams and 4 sires
#> Transferring input pedigree ...
#>  
#> ℹ Calculating LL for  dam_paired
#> ℹ Conditioning on pedigree with 145 individuals, 5 dams and 4 sires
#> Transferring input pedigree ...
#>  
#> ℹ Calculating LL for  sire_paired
#> ℹ Conditioning on pedigree with 145 individuals, 5 dams and 4 sires
#> Transferring input pedigree ...
print(Ped_with_probs, digits=2)
#>            id         dam        sire birthyear Probdam dam_alt Probdam_alt
#> 1 i021_2002_M i001_2001_F i020_2001_M      2002       1      FS     2.4e-06
#> 2 i022_2002_F i015_2001_F i006_2001_M      2002       1      GP     2.8e-09
#> 3 i023_2002_F i007_2001_F i019_2001_M      2002       1      FS     7.9e-07
#> 4 i024_2002_M i013_2001_F        <NA>      2002      NA    <NA>          NA
#> 5 i025_2002_M i014_2001_F i057_2003_M      2002       1      GP     2.3e-08
#>   Probsire sire_alt Probsire_alt Probpair
#> 1    1e+00       HS      2.4e-08  1.0e+00
#> 2    1e+00       GP      9.3e-08  1.0e+00
#> 3       NA     <NA>           NA       NA
#> 4       NA     <NA>           NA       NA
#> 5    6e-34       HS      2.5e-01  6.7e-61
# Any non-genotyped non-'dummifiable' individuals are automatically skipped

# To get likelihoods for 'all' relationships, not just probabilities for
# PO & (next-)most-likely:
LL_sire_single <- CalcPairLL(
  Pairs = data.frame(id1=test_ped$id,
                     id2=test_ped$sire,
                     dropPar1='both', # drop both -> id2 as single parent
                     focal='PO'),
  Pedigree = Ped_griffin,   # pedigree to condition on
  GenoM = Geno_griffin, Plot=FALSE)
#> ℹ Conditioning on pedigree with 200 individuals, 167 dams and 163 sires
#> ! Assuming columns 1 and 2 of Pairs are 'ID1' and 'ID2'
#> Transferring input pedigree ...

Usage

Arguments

Value

Details

See also

Examples