MyNixOS website logo
Description

Epistatic Network Modelling with Forward-Time Simulation.

Allows for forward-in-time simulation of epistatic networks with associated phenotypic output.

epinetr

An R Package for Epistastic Network Modelling with Forward-Time Simulation

About this project

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

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.

Usage

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)

Authors and support

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 [email protected] for assistance.

Contributing

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

License

epinetr is released under the GPLv3 license. See the file LICENSE for more details.

Metadata

Version

0.96

License

Unknown

Platforms (75)

    Darwin
    FreeBSD
    Genode
    GHCJS
    Linux
    MMIXware
    NetBSD
    none
    OpenBSD
    Redox
    Solaris
    WASI
    Windows
Show all
  • aarch64-darwin
  • aarch64-genode
  • aarch64-linux
  • aarch64-netbsd
  • aarch64-none
  • aarch64_be-none
  • arm-none
  • armv5tel-linux
  • armv6l-linux
  • armv6l-netbsd
  • armv6l-none
  • armv7a-darwin
  • armv7a-linux
  • armv7a-netbsd
  • armv7l-linux
  • armv7l-netbsd
  • avr-none
  • i686-cygwin
  • i686-darwin
  • i686-freebsd
  • i686-genode
  • i686-linux
  • i686-netbsd
  • i686-none
  • i686-openbsd
  • i686-windows
  • javascript-ghcjs
  • loongarch64-linux
  • m68k-linux
  • m68k-netbsd
  • m68k-none
  • microblaze-linux
  • microblaze-none
  • microblazeel-linux
  • microblazeel-none
  • mips-linux
  • mips-none
  • mips64-linux
  • mips64-none
  • mips64el-linux
  • mipsel-linux
  • mipsel-netbsd
  • mmix-mmixware
  • msp430-none
  • or1k-none
  • powerpc-netbsd
  • powerpc-none
  • powerpc64-linux
  • powerpc64le-linux
  • powerpcle-none
  • riscv32-linux
  • riscv32-netbsd
  • riscv32-none
  • riscv64-linux
  • riscv64-netbsd
  • riscv64-none
  • rx-none
  • s390-linux
  • s390-none
  • s390x-linux
  • s390x-none
  • vc4-none
  • wasm32-wasi
  • wasm64-wasi
  • x86_64-cygwin
  • x86_64-darwin
  • x86_64-freebsd
  • x86_64-genode
  • x86_64-linux
  • x86_64-netbsd
  • x86_64-none
  • x86_64-openbsd
  • x86_64-redox
  • x86_64-solaris
  • x86_64-windows