Determination of an empirical null distribution of the QTL significance threshold for a MPP QTL analysis using permutation test (Churchill and Doerge, 1994).
mpp_perm(
mppData,
trait = 1,
Q.eff = "cr",
N = 1000,
q.val = 0.95,
verbose = TRUE,
n.cores = 1
)Return:
List with the following object:
Vector of the highest genome-wide -log10(p-values).
Quantile values from the QTL significance threshold null distribution.
Numeric vector of random generated seed values for each
permutation.
An object of class mppData.
Numerical or character indicator to specify which
trait of the mppData object should be used. Default = 1.
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".
Number of permutations. Default = 1000.
Single numeric value or vector of desired quantiles from
the null distribution. Default = 0.95.
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.
Numeric. Specify here the number of cores you like to
use. Default = 1.
Vincent Garin
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.
Churchill, G. A., & Doerge, R. W. (1994). Empirical threshold values for quantitative trait mapping. Genetics, 138(3), 963-971.
mpp_SIM
data(mppData)
Perm <- mpp_perm(mppData = mppData, Q.eff = "cr", N = 5)
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