Description Usage Arguments Details Value References See Also Examples
grm.pair
computes relatedness estimates between two individuals.
1 2 |
geno1, geno2 |
numeric vector. |
freq |
numeric vector, values between 0 and 1. |
method |
string. |
weights |
numeric vector, values between 0 and 1. |
init.est |
numeric. |
geno1
and geno2
are vectors of counts of reference alleles. freq
is the vector of reference allele frequencies.
The default method
is "twostep", other options include "classic", "robust" and "general". When using the default "twostep" method, user can supply an initial estimate through init.est
to bypass the first step. When "general" is selected, weights
must also be specified. The difference between the two-step GRM, classic GRM and robust GRM is discussed in Wang et al. (2017).
An estimate of realized relatedness.
Wang et al. (2017) Genetics 205:1063-1078, https://www.ncbi.nlm.nih.gov/pubmed/28100587.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | # simulate genotypes for a full sib pair
pedigree = as.character(rep(1, 4))
member = as.character(c(11, 12, 21, 22))
sex = as.numeric(c(1, 2, 1, 2))
father = as.character(c(NA, NA, 11, 11))
mother = as.character(c(NA, NA, 12, 12))
pedinfo = data.frame(pedigree, member, sex, father, mother, stringsAsFactors = FALSE)
set.seed(1)
inher = sim.recomb(pedinfo, 3500) # on a hypothetical chromosome
nsnp = 100000
marker = seq(0,3500,length.out=nsnp)
freq = runif(nsnp, 0.05, 0.95)
haplo = sim.haplotype(freq, 4)
geno = populate.snp(inher, haplo, marker, output.allele = FALSE)
# simulation truth
ibd.proportion(inher,3,4)
# different GRM estimates
grm.pair(geno[3,], geno[4,], freq, method = "twostep")
grm.pair(geno[3,], geno[4,], freq, method = "classic")
grm.pair(geno[3,], geno[4,], freq, method = "robust")
grm.pair(geno[3,], geno[4,], freq, method = "general", weights = sample(freq, nsnp)/sum(freq))
# compute the relatedness matrix
grm.matrix(geno, freq)
grm.matrix(geno, freq, method = "robust")
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