inbreedR (version 0.3.0)

r2_Wf: Expected r2 between inbreeding level (f) and fitness (W)

Description

Expected r2 between inbreeding level (f) and fitness (W)

Usage

r2_Wf(genotypes, trait, family = "gaussian", type = c("msats", "snps"),
  nboot = NULL, parallel = FALSE, ncores = NULL, CI = 0.95)

Arguments

genotypes
data.frame with individuals in rows and loci in columns, containing genotypes coded as 0 (homozygote), 1 (heterozygote) and NA (missing).
trait
vector of any type which can be specified in R's glm() function
family
distribution of the trait. Default is gaussian. For other distributions, just naming the distribution (e.g. binomial) will use the default link function (see ?family). Specifying another link function can be done in the same way as in the glm() function.
type
specifies g2 formula to take. Type "snps" for large datasets and "msats" for smaller datasets.
nboot
number of bootstraps over individuals to estimate a confidence interval around r2(W, f).
parallel
Default is FALSE. If TRUE, bootstrapping and permutation tests are parallelized.
ncores
Specify number of cores to use for parallelization. By default, all available cores but one are used.
CI
confidence interval (default to 0.95)

Value

  • callfunction call.
  • exp_r2_fullexpected r2 between inbreeding and sMLH for the full dataset
  • r2_Wf_bootexpected r2 values from bootstrapping over individuals
  • CI_bootconfidence interval around the expected r2
  • nobsnumber of observations
  • nlocnumber of markers

References

Slate, J., David, P., Dodds, K. G., Veenvliet, B. A., Glass, B. C., Broad, T. E., & McEwan, J. C. (2004). Understanding the relationship between the inbreeding coefficient and multilocus heterozygosity: theoretical expectations and empirical data. Heredity, 93(3), 255-265.

Szulkin, M., Bierne, N., & David, P. (2010). HETEROZYGOSITY-FITNESS CORRELATIONS: A TIME FOR REAPPRAISAL. Evolution, 64(5), 1202-1217.

Examples

Run this code
data(mouse_msats)
data(bodyweight)
genotypes <- convert_raw(mouse_msats)

(out <- r2_Wf(genotypes = genotypes, trait = bodyweight, family = "gaussian", type = "msats",
              nboot = 100, parallel = FALSE, ncores = NULL, CI = 0.95))

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