mppR (version 1.2.1)

MQE_proc: Multi-QTL effect MPP analysis

Description

Build multi-QTL effects (MQE) models in which different QTL effects (cross-specific, parental, ancestral or bi-allelic) can be assumed at different loci.

Usage

MQE_proc(pop.name = "MPP_MQE", trait.name = "trait1", mppData = NULL,
  trait = 1, Q.eff, threshold = 4, window = 30, backward = TRUE,
  alpha.bk = 0.05, plot.MQE = FALSE, n.cores = 1, verbose = TRUE,
  output.loc)

Arguments

pop.name

Character name of the studied population. Default = "MPP_MQE".

trait.name

Character name of the studied trait. Default = "trait1".

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 vector of possible QTL effects the user want to test. Elements of Q.eff can be "cr", "par", "anc" or "biall". For details look at mpp_SIM.

threshold

Numeric value representing the -log10(p-value) threshold above which a position can be considered as significant. Default = 4.

window

Numeric distance (cM) on the left and the right of a cofactor position where it is not included in the model. Default = 30.

backward

Logical value. If backward = TRUE, the function performs a backward elimination on the list of selected QTLs. Default = TRUE.

alpha.bk

Numeric value indicating the significance level for the backward elimination. Default = 0.05.

plot.MQE

Logical value. If plot.MQE = TRUE, the function will plot the last run of the MQE model determination. Default = FALSE.

n.cores

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

verbose

Logical value indicating if the steps of MQE_proc should be printed. Default = TRUE.

output.loc

Path where a folder will be created to save the results.

Value

Return:

List containing the following items:

n.QTL

Number of detected QTLs.

QTL

Data.frame with QTL positions.

R2

list containing R squared statistics of the QTL effects. for details see QTL_R2.

QTL.effects

List of genetic effects per QTL.

Some output files are also saved at the location specified (output.loc):

A QTL report (QTL_REPORT.txt) with: 1) the number of detected QTLs; 2) the global R squared statistics; 3) for each QTL, position information and estimated QTL genetic effect per cross or parents.

The list of QTLs (QTL.txt).

The QTL R squared statistics (QTL_R2.txt) (for details see QTL_R2).

General results of the QTL detection process: Number of QTL and global adjusted and non-adjusted R squared statistics. (QTL_genResults.txt).

if plot.MQE = TRUE, a plot of the last QTL detection run profile (plot_MQE.pdf).

Details

The possible QTL effect that the user wants to allow must be specified in Q.eff. The procedure is the following:

1. Forward regression to determine a MQE model with different possible assumptions for the QTL effect at different loci. The function use.

2. Optional backward elimination (backward = TRUE) on the final list of detected QTLs.

3. Estimation of the QTL genetic effects and R squared statistics.

4. Optional plot (plot.MQE = TRUE) of the last CIM run of the forward regression using the function.

See Also

mpp_perm, mpp_SIM, QTL_R2

Examples

# NOT RUN {
data(mppData)

# Specify a location where your results will be saved
my.loc <- tempdir()

MQE <- MQE_proc(pop.name = "USNAM", trait.name = "ULA", mppData = mppData,
                Q.eff = c("par", "biall"), verbose = FALSE,
                output.loc = my.loc)
                 

# }