mpp_perm {mppR}

QTL significance threshold by permutation

Description

Determination of an empirical null distribution of the QTL significance threshold for a MPP QTL analysis using permutation test (Churchill and Doerge, 1994).

Usage

mpp_perm(
  mppData,
  trait = 1,
  Q.eff = "cr",
  N = 1000,
  q.val = 0.95,
  verbose = TRUE,
  n.cores = 1
)

Arguments

mppData

An object of class mppData.

trait

Numerical or character indicator to specify which trait of the mppData object should be used. Default = 1.

Q.eff

Character expression indicating the assumption concerning the QTL effects: 1) "cr" for cross-specific; 2) "par" for parental; 3) "anc" for ancestral; 4) "biall" for a bi-allelic. For more details see mpp_SIM. Default = "cr".

N

Number of permutations. Default = 1000.

q.val

Single numeric value or vector of desired quantiles from the null distribution. Default = 0.95.

verbose

Logical value indicating if progression of the function should be printed. It will not affect the printing of the other functions called by mpp_perm(), especially the printing of asreml(). Default = TRUE.

n.cores

Numeric. Specify here the number of cores you like to use. Default = 1.

Details

Performs N permutations of the trait data and computes each time a genome-wide QTL profile. For every run, it stores the highest -log10(p-val). These values can be used to build a null distribution for the QTL significance threshold. Quantile values can be determined from the previous distribution. For more details about the different possible models and their assumptions see mpp_SIM documentation.

Value

Return:

List with the following object:

max.pval

Vector of the highest genome-wide -log10(p-values).

q.val

Quantile values from the QTL significance threshold null distribution.

seed

Numeric vector of random generated seed values for each permutation.

Author(s)

Vincent Garin

References

Churchill, G. A., & Doerge, R. W. (1994). Empirical threshold values for quantitative trait mapping. Genetics, 138(3), 963-971.

See Also

mpp_SIM

Examples

data(mppData)

Perm <- mpp_perm(mppData = mppData, Q.eff = "cr", N = 5)