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Estimate haplotype frequencies and LD statistics from two biallelic variants

Source: R/estimate_ld.R
estimate_ld.Rd

Genotype data in R is usually loaded as genotype counts of biallelic variants. Accurately estimating haplotype frequencies without phase information is challenging. The key ambiguity is for double heterozygotes (1/1): you can't tell if the haplotypes are A1-B1/A2-B2 or A1-B2/A2-B1.

To estimate haplotype frequency without the underlying haplotype phase we can use the Expectation-Maximisation (EM) algorithm by Excoffier & Slatkin (1995) (https://doi.org/10.1093/oxfordjournals.molbev.a040269). This function estimates the haplotype frequencies and returns the R^2 and D' statistics.

Estimates highly similar to plink2 --r2-phased cols=+dprimeabs for several examples. This function is the combination of some of my older scripts plus input from Copilot.

Usage

estimate_ld(df, tol = 1e-08, max_iter = 1000)

Arguments

df

A data frame of exactly two cols - both must be integer vector (0, 1, 2) — minor allele counts for variant A and B

tol

Convergence tolerance for EM

max_iter

Maximum EM iterations

Value

A data.frame with haplotype freqs, allele freqs, D, D', and R²

Author

Luke Pilling

Examples


# Estimate LD between HFE p.C282Y and HFE p.S65C
ukb |> 
  dplyr::select(rs1800562_g_a, rs1800730_a_t) |> 
  estimate_ld()
#> Error: object 'ukb' not found
#>         P_A1B1     P_A1B2     P_A2B1    P_A2B2       p_A1      p_A2       p_B1     p_B2            D       D_max    D_prime unsigned_D_prime   R_squared em_iterations
#> 1 3.203526e-05 0.07335235 0.01563897 0.9109766 0.07338439 0.9266156 0.01567101 0.984329 -0.001117972 0.001150007 -0.9721434        0.9721434 0.001191575           110