adegenet (version 1.3-5)

glSim: Simulation of simple genlight objects

Description

The function glSim simulates simple SNP data with the possibility of contrasted structures between two groups. Returned objects are instances of the class genlight.

Usage

glSim(n.ind, n.snp.nonstruc, n.snp.struc = 0, grp.size = round(n.ind/2), 
    ploidy = 1, alpha = 0, block.size = NULL, LD = FALSE, ...)

Arguments

n.ind

an integer indicating the number of individuals to be simulated.

n.snp.nonstruc

an integer indicating the number of non-structured SNPs to be simulated; for these SNPs, all individuals are drawn from the same binomial distribution.

n.snp.struc

an integer indicating the number of structured SNPs to be simulated; for these SNPs, different binomial distributions are used for the two simulated groups; frequencies of the derived alleles in groups A and B are built to differ (see deta

grp.size

an integer indicating the size of the first group of individuals (noted 'A'); by default, both groups have the same size.

ploidy

an integer indicating the ploidy of the simulated genotypes.

alpha

asymmetry parameter: a numeric value between 0 and 0.5, used to enforce allelic differences between the groups (see details); ignored if LD=TRUE.

block.size

an optional integer indicating the number of SNPs to be handled at a time during the simulations. By default, all SNPs are simulated at the same time, but RAM can limit this operation. Using blocks of a few hundred or thousand SNPs decreases

LD

a logical indicating whether loci should be displaying linkage disequilibrium (TRUE) or be generated independently (FALSE, default). When set to TRUE, data are generated by blocks of correlated SNPs (see details).

...

arguments to be passed to the genlight constructor.

Value

• A genlight object.

encoding

UTF-8

Details

=== Allele frequencies in contrasted groups === When n.snp.struc is greater than 0, some SNPs are simulated in order to differ between groups (noted 'A' and 'B'). Such differences can be achieved differently depending on whether loci are independent (LD=FALSE), or not (LD=TRUE). In the first case, different patterns between groups are achieved by using different frequencies of the second allele for A and B, denoted $p_A$ and $p_B$. For a given SNP, $p_A$ is drawn from a uniform distribution between 0 and (0.5 - alpha). $p_B$ is then computed as 1 - $p_A$. Therefore, differences between groups are mild for alpha=0, and total for alpha = 0.5.

Whenever loci are linked (LD=TRUE), this option is no longer available. Differences between groups merely occur by drawing alleles from randomly generated, group-specific allele frequencies.

=== Linked or independent loci === Independent loci (LD=FALSE) are simulated using the standard binomial distribution, with randomly generated allele frequencies. Linked loci (LD=FALSE) are trickier towe need to simulate discrete variables with pre-defined correlation structure.

Here, we first generate deviates from multivariate normal distributions with randomly generated correlation structures. These variables are then discretized using the quantiles of the distribution. Further improvement of the procedure will aim at i) specifying the strength of the correlations between blocks of alleles and ii) enforce contrasted structures between groups.

See Also

- genlight: class of object for storing massive binary SNP data.

- glPlot: plotting genlight objects.

- glPca: PCA for genlight objects.

Examples

## no structure
x <- glSim(100, 1e3, ploid=2)
plot(x)

## 1,000 non structured SNPs, 100 structured SNPs
x <- glSim(100, 1e3, n.snp.struc=100, ploid=2)
plot(x)

## 1,000 non structured SNPs, 100 structured SNPs, ploidy=4
x <- glSim(100, 1e3, n.snp.struc=100, ploid=4)
plot(x)

## same thing, stronger differences between groups
x <- glSim(100, 1e3, n.snp.struc=100, ploid=2, alpha=0.4)
plot(x)

##  same thing, loci with LD structures
x <- glSim(100, 1e3, n.snp.struc=100, ploid=2, alpha=0.4, LD=TRUE, block.size=100)
plot(x)