Description Usage Arguments Value Author(s) References Examples
Expected r2 between standardized multilocus heterozygosity (h) and inbreeding level (f)
1 2 
genotypes 

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(h, 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) 
call 
function call. 
r2_hf_full 
expected r2 between inbreeding and sMLH for the full dataset 
r2_hf_boot 
expected r2 values from bootstrapping over individuals 
CI_boot 
confidence interval around the expected r2 
nobs 
number of observations 
nloc 
number of markers 
Martin A. Stoffel (martin.adam.stoffel@gmail.com)
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), 255265.
Szulkin, M., Bierne, N., & David, P. (2010). HETEROZYGOSITYFITNESS CORRELATIONS: A TIME FOR REAPPRAISAL. Evolution, 64(5), 12021217.
1 2 3 4  data(mouse_msats)
genotypes < convert_raw(mouse_msats)
(out < r2_hf(genotypes, nboot = 100, type = "msats", parallel = FALSE))
plot(out)

20 bootstraps over individuals done
40 bootstraps over individuals done
60 bootstraps over individuals done
80 bootstraps over individuals done
100 bootstraps over individuals done
### bootstrapping over individuals finished! ###
Calculation of expected r2 between inbreeding level (f) and heterozygosity (sMLH)

Data: 36 observations at 12 markers
Function call = r2_hf(genotypes = genotypes, type = "msats", nboot = 100, parallel = FALSE)
Expected r2 based on all markers: 0.2797576
Confidence interval for r2 based on bootstrapping over individuals:
2.5% 97.5%
0.0000000 0.4951413
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