insecticide resistance population genetics model as an R package
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DESCRIPTION
NAMESPACE
README.md
resistance.Rproj

README.md

resistance

An insecticide resistance population genetics model with 2 loci and 2 insecticides.

Development by Andy South, Ian Hastings and Beth Levick, 2015-8.

The model is described here :

South, A., & Hastings, I. M. (2018). Insecticide resistance evolution with mixtures and sequences : a model-based explanation. Malaria Journal. https://doi.org/10.1186/s12936-018-2203-y

Levick, B., South, A., & Hastings, I. M. (2017). A two-locus model of the evolution of insecticide resistance to inform and optimise public health insecticide deployment strategies. PLoS Computational Biology, 13, e1005327. https://doi.org/10.1371/journal.pcbi.1005327.

The code is licensed GPL-3, please cite the paper above if you use it.

Running the code is slightly involved, you may want to explore the user interfaces below first.

Installation

#install.packages("devtools")
require(devtools)    
install_github('AndySouth/resistance')  
require(resistance)

User Interfaces

#install.packages("shiny")
require(shiny) 
UImix: allows 2 scenarios of mixture and sequential to be compared and modified
runUImix()       
UI1: single scenario, mixture, show all 4 loci
runUI1() 
UI2: effect of sex-linkage on a mixture
runUI2() 
UI3: recreates Curtis(1985) Fig2 and allows params to be varied to modify the plot
runUI3()

Main functions to run the model

# Run model scenarios specified in an input object
input <- setInputOneScenario(P_1=0.01)
listOut <- runModel2(input, produce.plots = TRUE)

# Recreate figure 2 of Curtis(1985), allows inputs to be tweaked
runcurtis_f2()

Code to reproduce figures and text for South & Hastings (2018)

South and Hastings 2018, reproducible.

Sensitivity analysis for Levick, South & Hastings (2017)

# inst/documents/sensiAnPaper1All.Rmd
# an rmarkdown file that runs all of the sensitivity analysis for paper1
# it runs the model itself like in this example :
nScenarios <- 3 

listOutMix <- sensiAnPaperPart( nScenarios, insecticideUsed = 'mixture' )
listOutI1 <- sensiAnPaperPart( nScenarios, insecticideUsed = 'insecticide1' )
listOutI2 <- sensiAnPaperPart( nScenarios, insecticideUsed = 'insecticide2' )

# sensiAnPaperPart() contains hardcoded input ranges
# it generates random numbers and repeatedly calls setInputOneScenario()
# then it calls runModel2() to run the model using these inputs

# all figures for Levick, South & Hastings (2017)
# inst/documents/paper1/paper1_results_figs_slimmed_50_rr.Rmd