LLtoProb: transform log-likelihoods to probabilities

In sequoia: Pedigree Inference from SNPs

transform log-likelihoods to probabilities

Description

transform a vector with log10 likelihoods to a vector with probabilities summing to one.

Usage

LLtoProb(LLv)

Arguments

LLv	a vector with log10-likelihoods. All values >0 are set to NA.

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.

Computational under/overflow issues are reduced by subtracted the maximum value before converting from log to regular scale. Probabilities that would still be smaller than the machine precision ((LL - min(LL)/2) < log10(.Machine$double.xmin)) are set to NA en then to 0, instead of -Inf, to avoid issues when scaling to sum to 1.

Value

a vector with probabilities, with the same length and names.

Examples

LL_pairs <- CalcPairLL(data.frame(ID1='i042_2003_F',
                         ID2=c('i015_2001_F', 'i022_2002_F', 'i035_2002_F')),
                  GenoM = Geno_griffin, Complex='simp', Err=1e-3, Plot=FALSE)
prob_pairs <- plyr::aaply(as.matrix(LL_pairs[,10:16]), .margin=1, LLtoProb)
round(prob_pairs, 3)
# i035_2002_F is MHS of i042_2003_F, but when not conditioning on any other
# relatives has a higher LL to be 3rd degree relative (HA)
# (possibly genotyping errors, or just randomness of Mendelian inheritance)

sequoia documentation built on Aug. 21, 2025, 5:43 p.m.