| snpgdsLDpair {SNPRelate} | R Documentation |
Return a LD value between snp1 and snp2.
snpgdsLDpair(snp1, snp2, method = c("composite", "r", "dprime", "corr"))
snp1 |
a vector of SNP genotypes (0 – BB, 1 – AB, 2 – AA) |
snp2 |
a vector of SNP genotypes (0 – BB, 1 – AB, 2 – AA) |
method |
"composite", "r", "dprime", "corr", see details |
Four methods can be used to calculate linkage disequilibrium values: "composite" for LD composite measure, "r" for R coefficient (by EM algorithm assuming HWE, it could be negative), "dprime" for D', and "corr" for correlation coefficient. The method "corr" is equivalent to "composite", when SNP genotypes are coded as: 0 – BB, 1 – AB, 2 – AA.
Return a numeric vector:
ld |
a measure of linkage disequilibrium |
if method = "r" or "dprime",
pA_A |
haplotype frequency of AA, the first locus is A and the second locus is A |
pA_B |
haplotype frequency of AB, the first locus is A and the second locus is B |
pB_A |
haplotype frequency of BA, the first locus is B and the second locus is A |
pB_B |
haplotype frequency of BB, the first locus is B and the second locus is B |
Xiuwen Zheng
Weir B: Inferences about linkage disequilibrium. Biometrics 1979; 35: 235-254.
Weir B: Genetic Data Analysis II. Sunderland, MA: Sinauer Associates, 1996.
Weir BS, Cockerham CC: Complete characterization of disequilibrium at two loci; in Feldman MW (ed): Mathematical Evolutionary Theory. Princeton, NJ: Princeton University Press, 1989.
# open an example dataset (HapMap) genofile <- snpgdsOpen(snpgdsExampleFileName()) snp1 <- read.gdsn(index.gdsn(genofile, "genotype"), start=c(1,1), count=c(1,-1)) snp2 <- read.gdsn(index.gdsn(genofile, "genotype"), start=c(2,1), count=c(1,-1)) snpgdsLDpair(snp1, snp2, method = "composite") snpgdsLDpair(snp1, snp2, method = "r") snpgdsLDpair(snp1, snp2, method = "dprime") snpgdsLDpair(snp1, snp2, method = "corr") # close the genotype file snpgdsClose(genofile)