eqtl (version 1.1-7)

gpt: Global Permutation Threshold

Description

Computes a Global Permutation Threshold to estimate a LOD score significance threshold.

Usage

gpt(cross, n_etrait=100, n_perm=1000)

Arguments

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.

Value

scanoneperm

Details

Computes the 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).

References

Churchill and Doerge (1994) Empirical threshold values for quantitative trait mapping. Genetics 138:963-971

See Also

read.cross,scanone,add.threshold

Examples

data(seed10);

# Compute the global permutation test with 1000 permutations on 100 individuals
## Not run: 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)

out_100.gpt

# Significance LOD threshold value with alpha at 0.05 (5%)
## Not run: th_1000 <- as.numeric(out_1000.gpt)[order(out_1000.gpt,decreasing=TRUE)][5000];
 th_100 <- as.numeric(out_100.gpt)[order(out_100.gpt,decreasing=TRUE)][5];

th_100

hist(unclass(out_100.gpt),nclass=50,col='gray')
abline(v=th_100,col='red')

# out.em <- scanone(seed10, method='hk', chr=c(1:5));
## Not run: 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");## End(Not run)