Usage
popRangeSim(world, popSize, rMean = 0, rVar = 0, A = 0, K = 100, catProb = 0,
diploid = TRUE, nGens = 100, migration = 0, SNP_model = 1, h = 0.5, s = 0,
gamma_shape = NULL, gamma_scale = NULL, gSize = NULL, mutRate = NULL,
nSNPs = NULL, SNPs_starting_freq = NULL, GENEPOP = FALSE, GENELAND = FALSE,
PLINK = FALSE, outfile = "", infile = NULL, recordTrag = 0, sDiff = NULL)
Arguments
world
This matrix grid defines the grid of populations. Each point in the matrix defines a potential population. A 1 indicates a population may exist at that point. -1 indicates no population can exist at that grid point. This allows the user to define a pop
popSize
Starting population size. If numeric, every existing population has the same size. If matrix, each population size is defined separately. Input must be an integer >= 0 or a matrix of integers >= 0.
rMean
Mean r (from exponential growth equation). Float between c(0,1). If numeric, all populations have the same r. If matrix, each population has its own r.
rVar
Variance in r. Float between c(0,1). If numeric, all populations have the same variance. If matrix, each population has its own r. Set to 0 if you want r to be exactly rMean each generation.
A
Allee Effect. If numeric, all populations have same Allee effect. If matrix, each population has its own Allee effect. Set to 0 if you do not want to incorporate the Allee effect
K
Carry capacity. If int, all populations have same carry capacity. If matrix, each population has its own carrying capacity.
catProb
Probability of population extinction each generation (range:0-1). If a numeric, all populations have the same catProb. If matrix, each population has its own catProb.
diploid
Ploidy of individuals. Two options: haploid and diploid. If TRUE, diploid. If FALSE, haploid.
nGens
Int, number of generations for the simulations to run.
migration
Probability of each individual migrating each generation. If float, every population has same migration rate. Each migration randomly picks on adjacent viable grid point to migrate to (diagonals included). Alternatively, a matrix can be provided. The fi
SNP_model
There are two options. The first option (0) indicates that the user will provide starting SNP frequencies. The second option (1) determines starting SNP frequencies according to the standard neutral model with user provided genome size and mutation rate.
h
Dominance parameter. (Only relevant for diploids.)
s
If numeric, all SNPs have the same selection coefficient. If matrix, first 2 columns define starting and ending SNP. The 3rd column is the selection coefficient for those SNPs.
gamma_shape
Alpha parameters to the gamma distribution. NOTE: Provide EITHER an s input OR gamma_a, gamma_b values.
gamma_scale
Beta parameters to the gamma distribution. NOTE: Provide EITHER an s input OR gamma_a, gamma_b values.
gSize
Number of base pairs in the genome. (Required if SNP_Model = 1)
mutRate
Mutation rate per generation per site. (Required if SNP_Model = 1)
nSNPs
Number of SNPs, if SNP_Model = 0. (Required if SNP_Model = 0)
SNPs_starting_freq
The initial frequency of the SNPs (range:0-1). If int, all SNPs are given the same starting frequencies. If matrix, columns 1 and 2 indicate the first and last SNPs. Column 3 indicates the allele frequency of these SNPs. (Required if SNP_Model = 0)
GENEPOP
If TRUE, write results to GENEPOP formatted file.
GENELAND
If TRUE, write results to GENELAND formatted file.
PLINK
If TRUE, write results to an PLINK formatted file
outfile
A string of the outfile name.
infile
If you have already ran a simulation, you can use the results file as input. This allows for temporally variable parameters and to output the state of the population at various time points.
recordTrag
If n, this records the trajectory of all of the alleles n generations and outputs them to a file. NOTE: If you have many SNPs or populations, this option may significantly increase simulation time. Also if you are using SNP_model=1, alleles that have a
sDiff
Defines the selection coefficients for each SNP in each population. This allows for spatially variable selection coefficients. The first line of the matrix consists of the strings sSNP and fSNP. These are the first and last SNPs with a specific set of