gpt {eqtl} | R Documentation |
Computes a Global Permutation Threshold to estimate a LOD score significance threshold.
gpt(cross, n_etrait=100, n_perm=1000)
cross |
An object of class cross . See 'qtl' package manual for read.cross function details. |
n_etrait |
An integer which specifies the number of individuals on which the permutation test are performed. |
n_perm |
An integer. This argument defines the number of permutation replicates. |
Computes a Global Permutation Threshold which fits to a single-QTL scan (using scanone
function) by permuting the phenotypes while maintaining the genotype for a sample of individuals randomly chosen within an object of class cross
. The GPT estimates the LOD score significance threshold if 1000 permutations at least are computed on 100 individuals at least (i.e. 100,000 permutations).
An object of class scanoneperm
Hamid A. Khalili
Churchill and Doerge (1994) Empirical threshold values for quantitative trait mapping. Genetics 138:963-971
read.cross
,scanone
,add.threshold
data(seed10); # Genotype probabilities seed10 <- calc.genoprob( cross=seed10, step=2, off.end=0, error.prob=0, map.function='kosambi', stepwidth='fixed'); seed10 <- sim.geno( cross=seed10, step=2, off.end=0, error.prob=0, map.function='kosambi', stepwidth='fixed'); # Compute the global permutation test with 1000 permutations on 100 individuals # out_1000.gpt <- gpt(seed10,100,1000); # Compute the global permutation threshold with 100 permutations on 100 individuals out_100.gpt <- gpt(seed10, 10, 10) # Significance LOD threshold value with alpha at 0.05 (5 # th_1000 <- out_1000.gpt[order(out.gpt,decreasing=TRUE)][5000]; th_100 <- out_100.gpt[order(out_100.gpt,decreasing=TRUE)][50]; th_100; mean(summary(out_100.gpt, alpha=0.05)); hist(out_100.gpt,nclass=50,col='gray') abline(v=th_100,col='red') # out.em <- scanone(seed10, method='em', chr=c(1:5)); # plot(out.em, chr=c(1:5)); # add.threshold(out.em, chr=c(1:5), perms=out_1000.gpt, alpha=0.05); # add.threshold(out.em, chr=c(1:5), perms=out_1000.gpt, alpha=0.1, col="green");