Analysing Inbreeding Based on Genetic Markers

A framework for analysing inbreeding and heterozygosity-fitness correlations (HFCs) based on microsatellite and SNP markers.

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inbreedR provides functions and workflows for the analysis of inbreeding and heterozygosity-fitness correlations (HFCs) based on molecular markers such as microsatellites and SNPs. It has four main application areas:

  • Quantifying variance in inbreeding through estimation of identitiy disequilibria (g2), heterozygosity-heterozygosity correlations (HHC) and variance in standardized multilocus heterozygosity (sMLH)

  • Calculating g2 for small and large SNP datasets. The use of data.table and parallelization speed up bootstrapping and permutation tests

  • Estimating central parameters within HFC theory, such as the influence of inbreeding on heterozygosity and fitness, and their confidence intervals.

  • Exploring the sensitivity of these measures towards the number of genetic markers using simulations

You can install:

  • the latest released version from CRAN with

  • the latest development version from github with

    if (packageVersion("devtools") < 1.6) {
    devtools::install_github("mastoffel/inbreedR", build_vignettes = TRUE)

If you encounter bug or if you have any suggestions for improvement, just contact me: martin.adam.stoffel[at]

Get started with inbreedR

To get started read the vignette:

vignette("inbreedR_step_by_step", package = "inbreedR")


Reference manual

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0.3.2 by Martin A. Stoffel, 2 years ago

Browse source code at

Authors: Martin A. Stoffel [aut, cre], Mareike Esser [aut], Joseph Hoffman [aut], Marty Kardos [aut]

Documentation:   PDF Manual  

GPL-2 license

Imports data.table, parallel, stats, graphics

Suggests testthat, knitr, rmarkdown

See at CRAN