inbreedR
contains the following functions:g2_microsats g2_snps convert_raw check_data r2_hf r2_Wf HHC sMLH MLH simulate_g2 simulate_r2_hf plot.inbreed print.inbreed
$$r(W, h) = r(W, f)r(h, f)$$
Estimating these parameters and their sensitivity towards the number and type of genetic markers used is the central framework of the inbreedR package. At the heart of measuring inbreeding based on genetic markers is the g2 statistic, which estimates the correlation of heterozygosity across markers, called identity disequilibrium (ID). ID is a proxy for inbreeding.
The package has three main goals:
For a short introduction to inbreedR start with the vignette:
browseVignettes(package = "inbreedR")
Szulkin, M., Bierne, N., & David, P. (2010). HETEROZYGOSITY-FITNESS CORRELATIONS: A TIME FOR REAPPRAISAL. Evolution, 64(5), 1202-1217.
David, P., Pujol, B., Viard, F., Castella, V. and Goudet, J. (2007), Reliable selfing rate estimates from imperfect population genetic data. Molecular Ecology, 16: 2474
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.