evola-package {evola} | R Documentation |
The evola package is nice wrapper of the AlphaSimR package that enables the use of the evolutionary algorithm to solve complex questions in a simple form.
The evolafit
function is the core function of the package which allows the user to specify the problem and constraints to find a close-to-optimal solution using the evolutionary forces.
The evola package is updated on CRAN every 4-months due to CRAN policies but you can find the latest source at https://github.com/covaruber/evola. This can be easily installed typing the following in the R console:
library(devtools)
install_github("covaruber/evola")
This is recommended if you reported a bug, was fixed and was immediately pushed to GitHub but not in CRAN until the next update.
For tutorials on how to perform different analysis with evola please look at the vignettes by typing in the terminal:
vignette("evola.intro")
The package has been equiped with several datasets to learn how to use the evola package:
* DT_technow
dataset to perform optimal cross selection.
* DT_wheat
dataset to perform optimal training population selection.
* DT_cpdata
dataset to perform optimal individual.
The machinery behind the scenes is AlphaSimR.
If you have any questions or suggestions please post it in https://stackoverflow.com or https://stats.stackexchange.com
I'll be glad to help or answer any question. I have spent a valuable amount of time developing this package. Please cite this package in your publication. Type 'citation("evola")' to know how to cite it.
Giovanny Covarrubias-Pazaran
Giovanny Covarrubias-Pazaran (2024). evola: a simple evolutionary algorithm for complex problems. To be submitted to Bioinformatics.
Gaynor, R. Chris, Gregor Gorjanc, and John M. Hickey. 2021. AlphaSimR: an R package for breeding program simulations. G3 Gene|Genomes|Genetics 11(2):jkaa017. https://doi.org/10.1093/g3journal/jkaa017.
Chen GK, Marjoram P, Wall JD (2009). Fast and Flexible Simulation of DNA Sequence Data. Genome Research, 19, 136-142. http://genome.cshlp.org/content/19/1/136.