Description Usage Arguments Value References Examples
Calculation of power is based on normal distribution.
At each selected QTL position, the probability of the corresponding
regression coefficient being different from zero is calculated using a
t-like test statistic which has normal distribution with mean
E(beta_k)/sqrt{Var(beta_k)}
and variance 1. Under the null hypothesis beta_k = 0
,
E(beta_k) = 0
.
Then, the mean value is returned as power.
1 | pwr.normtest(R, n, betaSE, lambda, pos, weights = 1, alpha = 0.01)
|
R |
(p x p) matrix containing theoretical correlation between SNP pairs |
n |
sample size |
betaSE |
effect size relative to residual standard deviation |
lambda |
shrinkage parameter |
pos |
vector (LEN nqtl) of SNP indices for assumed QTL positions |
weights |
weights vector (LEN p) of SNP-specific weights or scalar if weights are equal for all SNPs; default value 1 |
alpha |
type-I error level; default value 0.01 |
result
mean power at selected QTL positions
h2.le
QTL heritability under linkage-equilibrium assumption
h2.ld
QTL heritability under linkage-disequilibrium assumption
Wittenburg, Bonk, Doschoris, Reyer (2020) Design of Experiments for Fine-Mapping Quantitative Trait Loci in Livestock Populations. BMC Genetics 21:66. doi: 10.1186/s12863-020-00871-1
1 2 3 4 5 6 | ### correlation matrix (should depend on sire haplotypes)
R <- AR1(100, rho = 0.1)
### positions of putative QTL signals
pos <- c(14, 75)
### power at given sample size and other parameters
pwr.normtest(R, 100, 0.35, 1200, pos)
|
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