Marginal locus calculation {noia}

Estimation of parameters for specific allele frequencies

Description

This function computes some parameters of interest (mean phenotype, genetic variance, additive variance, and evolutionary change in additive variance) for a combination of allele frequencies, based on a genotype-phenotype map.

Usage

marginallocus(gmap, freq=NULL, what="mean", definition=11, mc.cores=1, ...)
## S3 method for class 'noia.marloc'
plot(x, xlab=NULL, ylim=NULL, ylab=attr(x, "what"), ...)
## S3 method for class 'noia.marloc'
image(x, xlab=NULL, ylab=NULL, zlim=NULL, 
      main=attr(x, "what"), col.max="red", col.min="blue", col.zero="white", 
      n.cols=1000, zeropart=0.01, contour.levels=10, contour.options=list(), ...) 

Arguments

gmap

Either an object of class noia.gpmap, or a vector of phenotypic values in the order defined as in genotypesNames

.

freq

A vector indicating the loci that should be analysed. See Details.

what

A character string among "mean", "varA", "varG", or "dvarA.dt".

definition

The number of allele frequencies to try for each locus.

mc.cores

If more than 1, the calculation is run on mc.cores cores via the library parallel.

x

An object of class noia.marloc obtained after running marginallocus.

col.max, col.min, col.zero

Colors standing for the maximal, minimal, and nil values, respectively. Setting col.zero to NULL generates a color gradient between col.min and col.max.

n.cols

Number of colors in the gradient.

zeropart

Width (relative to the full amplitude) of the region around zero which will be colored as col.zero.

contour.levels

Number of contour lines. Setting this to 0 leads to no contour lines.

contour.options

List of additional options to the contour function.

xlab, ylab, ylim, zlim, main

Classical parameters passed to plot and image.

...

Additional parameters to internal functions.

Details

marginallocus computes a population parameter for a series of allele frequencies. The loci under investigation are provided through the freq vector, which need to have as many elements as loci in the system. Values of the freq vector indicate fixed allele frequencies, while NA indicate loci under investigation. For instance, freq=c(NA, 1, NA, 0.5), will investigate the effect of varying loci 1 and 3, while keeping loci 2 and 4 at constant allele frequencies. The population is assumed to be at Hardy-Weinberg frequencies. If freq is not provided, all loci will be investigated.

Value

marginallocus returns an array with as many dimensions as loci under investigation. This array is an object of class "noia.marloc" which can be graphically illustrated through the provided plot (for 1-dimensional data) and image (for 2-dimensional data). Arrays of higher dimensionality cannot be represented graphically.

Author(s)

Arnaud Le Rouzic

See Also

linearGPmapanalysis

Examples

map <- c(0.25, -0.75, -0.75, -0.75, 2.25, 2.25, -0.75, 2.25, 2.25)

mrg2D <- marginallocus(map)
mrg1D <- marginallocus(map, freq=c(NA, 0)) # the second locus is fixed for allele 1

image(mrg2D)
plot(mrg1D)