inbreedR (version 0.2.0)

resample_g2: Identity disequilibrium (g2) for different subsets of markers

Description

Identity disequilibrium (g2) for different subsets of markers

Usage

resample_g2(genotypes, subsets = NULL, nboot = 100, type = c("msats",
  "snps"), parallel = FALSE, ncores = NULL)

Arguments

genotypes

data.frame with individuals in rows and loci in columns, containing genotypes coded as 0 (homozygote), 1 (heterozygote) and NA (missing)

subsets

a vector specifying the sizes of subsets to draw. For a subset of 20 markers, subsets = c(2, 5, 10, 15, 20) could be a reasonable choice. The minimum subset size is 2 and the maximum is the number of markers in the data.

nboot

number of re-draws per subset size.

type

specifies g2 formula to take. Type "snps" for large datasets and "msats" for smaller datasets.

parallel

Default is FALSE. If TRUE, resamplings are parallelized

ncores

Specify number of cores to use for parallelization. By default, all available cores are used.

Value

• call
  function call.
• g2_full
  g2 estimate for the full marker set
• all_g2_res
  vector of g2 values for each randomly subsetted dataset
• summary_exp_r2
  g2 mean and sd for each number of subsetted loci
• nobs
  number of observations
• nloc
  number of markers

References

Hoffman, J.I., Simpson, F., David, P., Rijks, J.M., Kuiken, T., Thorne, M.A.S., Lacey, R.C. & Dasmahapatra, K.K. (2014) High-throughput sequencing reveals inbreeding depression in a natural population. Proceedings of the National Academy of Sciences of the United States of America, 111: 3775-3780. Doi: 10.1073/pnas.1318945111

Examples

data(mouse_msats)
genotypes <- convert_raw(mouse_msats)
(out <- resample_g2(genotypes, subsets = c(2,4,6,8,10,12), nboot = 1000, type = "msats"))
plot(out)