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An R Package for Epistastic Network Modelling with Forward-Time Simulation
epinetr is a package for the R statistical computing environment designed to facilitate the modelling of epistasis and epistatic networks of arbitrary complexity in populations across generations. Our hope is that this software will aid researchers in uncovering the genetic architecture of complex traits and bridging the conceptual divide between quantitative and molecular genetics.
Using epinetr, you can test the impacts of various mixes of additive and epistatic effects against different population structures and selection criteria on populations. Our primary goal is to investigate the relationship between biological epistasis in individuals and additive models in populations.
Installation is straightforward, provided you already have the
devtools package installed. Simply run the command
install_github("diondetterer/epinetr")and the epinetr package will be installed into your R library.
There is a vignette in the package which provides a fairly comprehensive tutorial, and we encourage all users to read it. However, here are some minimal commands to get you started:
pop <- Population(
popSize = 500, map = map100snp, QTL = 20,
alleleFrequencies = runif(100), broadH2 = 0.9,
narrowh2 = 0.75, traitVar = 40
)This will create a Population object called
pop with 500 individuals, a chromosome map given by
map100snp, 20 randomly selected QTLs, randomly-generated
allele frequencies, broad-sense heritability at 0.9, narrow-sense
heritability at 0.75 and trait variance at 40.
pop <- addEffects(pop)
pop <- attachEpiNet(pop)These commands will attach additive and epistatic effects to the population.
plot(getEpiNet(pop))This will provide a visualisation of the epistatic network.
pop <- runSim(pop, generations = 150)This will run the simulator for 150 generations.
Finally, plot the run:
plot(pop)Dion Detterer, Paul Kwan and Cedric Gondro wrote the epinetr package, with Dion as the maintainer.
Issues can be reported via the issues tab, or you can email Dion at ddettere@myune.edu.au for assistance.
We welcome contributions to the project; please see the project wiki for details on the codebase.
For advice on setting up an appropriate R development environment, see Hadley Wickham’s advice on system setup at https://r-pkgs.org/setup.html
epinetr is released under the GPLv3 license. See the file
LICENSE for more details.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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