| simPheno {simulMGF} | R Documentation |
Function to simulate phenotypes
Description
Simulate a phenotype from a genotype matrix with QTLs with random effects sampled from a Normal distribution.
Usage
simPheno(x, Nqtl, Esigma, Pmean, Perror)
Arguments
x |
SNP matrix coded like 0 homozygous; 1 heterozygous; 2 homozygous |
Nqtl |
number of QTLs to simulate |
Esigma |
standard deviation of effects with distribution N~(0,Esigma^2) |
Pmean |
phenotype mean |
Perror |
standard deviation of error (portion of phenotype not explained by genomic information) |
Value
An object of class list containing the trait, the markers associated and their effects.
pheno |
vector with the trait values simulated. |
QTN |
column in the SNP matrix with the SNP associated. |
Meffects |
effects of the associated SNPs. |
Author(s)
Martin Nahuel Garcia <orcid:0000-0001-5760-986X>
References
Wu, R., Ma, C., & Casella, G. (2007). Statistical genetics of quantitative traits: linkage, maps and QTL. Springer Science & Business Media.
Examples
set.seed(123)
simGeno(100, 1000)
#' #[1] "simG was generated"
simPheno(simG, 50, .8, 12, .5)
#[1] "simP was generated"
str(simP)
#List of 3
#$ pheno : num [1:100, 1] 24 20.5 15.6 13.6 18.5 ...
#$ QTN : int [1:50] 568 474 529 349 45 732 416 51 413 514 ...
#$ Meffects: num [1:50] 0.2396 -0.138 0.906 0.0186 1.0687 ...