rSHAPE0.3.2 package

Simulated Haploid Asexual Population Evolution

addDrift

This is a simple little function used to represent drift by introducin...

addQuotes

This is a function to add quotation marks around each element of a cha...

adjustBirths

This function ensures that a vector of values will sum to a given numb...

birthFunction

This function calculates the number of births for the vector of popula...

buildPedigree

This is a convenience script to build an named list of empty lists, wh...

calc_relativeFitness

This is a function to calculate the relative fitness for a vector of f...

compute_distGrowth

This function is used to calculate the effect size and timing of the n...

create_genotypeFrame

This is a convenience function to ensure that we have a standard shape...

createGenotypes

This function searches the nearby mutational space of a focal genotype...

deathFunction

This allows SHAPE to simulate the death process as a deterministic val...

defineNeighbours

The function will identify the binary string of all possible neighbour...

defineSHAPE

These are some global reference options that SHAPE will use and I cons...

expGrowth

This function uses the exponential growth model and can either calcula...

extract_popDemographics

This is a function that steps forward through time steps of a SHAPE ru...

extractInfo_focalID

This is a function to extract genotype/lineage specific information. T...

find_neededNeighbours

This function querries if a suite of genotypes exist within the fitnes...

findParent

This function will look through a pedigree data.frame and recursively ...

fitnessDist

This is the function that will call for draws from distributions.

fitnessLandscape

This function will calculate the fitness values for genotypes being ne...

growthFunction

This is a wrapper function where the birth and death related parameter...

logisticGrowth

This function is simply an implementation of the logistic growth equat...

logisticMap

This is the discrete time logistic growth function known as the logist...

lossSampling

This function actually calculates the stochastic loss to populations.

mutationFunction

This allows SHAPE to simulate the mutation process as a deterministic ...

name_batchString

This function is used to build or split character string to be used fo...

name_batchSubmit

This is a function to programatically create R batch submission script...

name_bodyScript

This is a function to programatically create R script names

name_parameterScript

This is a function to programatically create R script names

name_subScript

This is a function to programatically create R batch submission script...

nameEnviron

This quick little function is a means for me to create the strings of ...

nameObject

This quick little function is a means for me to create the strings of ...

nameTable

This is a standardising function which allows SHAPE to programatiicall...

nameTable_neighbourhood

This is a standardising function which allows SHAPE to programatiicall...

nameTable_step

This is a standardising function which allows SHAPE to programatiicall...

querryEstablished

This function is used to find which elements of a population matrix ar...

reportPopulations

This is a convenience function to ensure that our population demograph...

reset_shapeDB

This is a convenience function to refresh connections to database file...

retrieve_binaryString

This is a function to search our mutational database and then find the...

runProcessing

This is a wrapper function to process a SHAPE run and extract meaningf...

runReplicate

This is the function that runs the main body, or meaningful execution,...

runSHAPE

This is the actual running of shape, it will initialise objects and va...

set_const_NK_interactionsMat

This is a function to just return a matrix that defines the sitewise d...

set_const_RMF_globalOptima

This function samples the space of all possible genotypes and then def...

set_DepbySite_ancestFitness

This is a convenience function for setting the dependent fitness value...

set_RMF_indWeight

In a RMF fitness landscape model, there is a weighting value applied t...

set_siteByState_fitnessMat

This function is designed to establish an initial object which maps th...

shapeCombinations

This is a function to take the input parameters and build the paramete...

shapeExperiment

This is a function used to read the SHAPE_experimentalDesign type inpu...

stopError

This is a convenience wrapper for sending an error and ending the SHAP...

summarise_evolRepeatability

This function will use output from summarise_experimentFiles and summa...

summarise_experimentFiles

This function will find all initially processed output files from indi...

summarise_experimentParameters

This function will use output from summarise_experimentFiles to locate...

summarise_popDemographics

This function will use output from summarise_experimentFiles and summa...

summariseExperiment

This function is a wrapper for getting a summary of the results of an ...

trimQuotes

This is a function to trim a string by removing the first and last cha...

updateLines

This is a function which is used to update lines that are searched and...

write_subScript

This function is used to programatically take vectors of paramters and...

writeParameters

This is a file for updating the post analysis plotting script and crea...

In silico experimental evolution offers a cost-and-time effective means to test evolutionary hypotheses. Existing evolutionary simulation tools focus on simulations in a limited experimental framework, and tend to report on only the results presumed of interest by the tools designer. The R-package for Simulated Haploid Asexual Population Evolution ('rSHAPE') addresses these concerns by implementing a robust simulation framework that outputs complete population demographic and genomic information for in silico evolving communities. Allowing more than 60 parameters to be specified, 'rSHAPE' simulates evolution across discrete time-steps for an evolving community of haploid asexual populations with binary state genomes. These settings are for the current state of 'rSHAPE' and future steps will be to increase the breadth of evolutionary conditions permitted. At present, most effort was placed into permitting varied growth models to be simulated (such as constant size, exponential growth, and logistic growth) as well as various fitness landscape models to reflect the evolutionary landscape (e.g.: Additive, House of Cards - Stuart Kauffman and Simon Levin (1987) <doi:10.1016/S0022-5193(87)80029-2>, NK - Stuart A. Kauffman and Edward D. Weinberger (1989) <doi:10.1016/S0022-5193(89)80019-0>, Rough Mount Fuji - Neidhart, Johannes and Szendro, Ivan G and Krug, Joachim (2014) <doi:10.1534/genetics.114.167668>). This package includes numerous functions though users will only need defineSHAPE(), runSHAPE(), shapeExperiment() and summariseExperiment(). All other functions are called by these main functions and are likely only to be on interest for someone wishing to develop 'rSHAPE'. Simulation results will be stored in files which are exported to the directory referenced by the shape_workDir option (defaults to tempdir() but do change this by passing a folderpath argument for workDir when calling defineSHAPE() if you plan to make use of your results beyond your current session). 'rSHAPE' will generate numerous replicate simulations for your defined range of experimental parameters. The experiment will be built under the experimental working directory (i.e.: referenced by the option shape_workDir set using defineSHAPE() ) where individual replicate simulation results will be stored as well as processed results which I have made in an effort to facilitate analyses by automating collection and processing of the potentially thousands of files which will be created. On that note, 'rSHAPE' implements a robust and flexible framework with highly detailed output at the cost of computational efficiency and potentially requiring significant disk space (generally gigabytes but up to tera-bytes for very large simulation efforts). So, while 'rSHAPE' offers a single framework in which we can simulate evolution and directly compare the impacts of a wide range of parameters, it is not as quick to run as other in silico simulation tools which focus on a single scenario with limited output. There you have it, 'rSHAPE' offers you a less restrictive in silico evolutionary playground than other tools and I hope you enjoy testing your hypotheses.

  • Maintainer: Jonathan Dench
  • License: GPL-3
  • Last published: 2019-07-19