This README file introduces HRitools, a package created by Héctor Puigdomènech Gómez. HRitools is a tool created in order to analyse adaptation and recombination data with the purpose of quantifying Hill-Robertson interference (HRi) with a curvilinear model, as suggested by Castellano et al. (2016).
In order to use HRitools in an R session, it must be installed. Dependencies must be installed previously. The mayority of packages can be installed as they are usually installed in R, but rtracklayer is a package inside Bioconductor, so its installation is a bit trickier. In fact, if Bioconductor is not installed in R, installation instructions can be found in this link. Then, all the dependencies can be simply installed by following these instructions.
install.packages(c("nls2","curl","ggplot2")) source("https://bioconductor.org/biocLite.R") biocLite("rtracklayer")
Once dependencies have been installed, devtools is the package required to install HRitools, as well as all the packages which are installed from Github.
install.packages("devtools") library(devtools) install_github("hectorpuigdo/HRitools")
Then, the library can simply be loaded with the comand
Three functions are included within the package: HRi, LVNLtest and rhokbPopFly. Each function has its own documentation, which can be found by, for example,
It is the primordial function of the package. It allows to calculate HRi curvilinear functions over an adapatation-recombination dataset ponderating with 0-fold sites. It simply needs a data frame with recombination, adaptation and 0-fold sites data points. Its usage is as simple as:
dataset <- data.frame(recombination,adapatation,fold0sites) HRi(dataset) #results can be stored in an object results <- HRi(dataset) #the function results contain several results, such as graphs, forumulas, and vectors results$Graph
This function is designed to calculate HRi curvilinear and linear models in order to compare them using Akaike information criterion. The same dataframe used with the function
HRi can be reused with this function such as:
This function provides five objects as a result: a data frame with AIC results, the result of an F-test, its significance level, and the results of generating both linear and curvilinear models.
This function is very useful for researchers who do not have the possibility to get expreimental Drosophila melanogaster population recombination data and need to find some population-scaled recombination data. Hervas et al. (2017) created PopFly, the Drosophila population genomics browser, and it contains a lot of recombination data from different populations, so
rhokbPopFly is a function to download and put recombination data into a data frame.
Population and window size must be specified, otherwise the Raleigh —RAL— population recombination dataset with a window size of 100kb is downloaded.
recombination_data <- rhokbPopFly("ZI","10kb")
Happy R coding!
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