QTL_effect_GE: MPP GxE QTL genetic effects

In vincentgarin/mppGxE: MPP GxE QTL analysis

MPP GxE QTL genetic effects

Description

Compute MPP GxE QTL genetic effects.

Usage

QTL_effect_GE(
  mppData,
  trait,
  Q.eff = "par",
  VCOV = "UN",
  QTL = NULL,
  maxIter = 100,
  msMaxIter = 100
)

Arguments

mppData	An object of class mppData.
trait	Character vector specifying which traits (environments) should be used.
Q.eff	Character expression indicating the assumption concerning the QTL effects: 1) "cr" for cross-specific; 2) "par" for parental; 3) "anc" for ancestral. Default = "par".
VCOV	VCOV Character expression defining the type of variance covariance structure used. 'CS' for compound symmetry assuming a unique genetic covariance between environments. 'CSE' for cross-specific within environment error term. 'CS_CSE' for both compound symmetry plus cross-specific within environment error term. 'UN' for unstructured environmental variance covariance structure allowing a specific genotypic covariance for each pair of environments. Default = 'UN'
QTL	Object of class QTLlist representing a list of selected marker positions obtained with the function QTL_select() or a vector of character marker positions names. Default = NULL.
maxIter	maximum number of iterations for the lme optimization algorithm. Default = 100.
msMaxIter	maximum number of iterations for the optimization step inside the lme optimization. Default = 100.

Value

Return:

Qeff	List of data.frame (one per QTL) containing the following information: QTL genetic effects Standard error of the QTL effects. Wald statistics of the effects. P-value of the test statistics. Significance of the QTL effects.

Author(s)

Vincent Garin

Examples

data(mppData_GE)

Qpos <- c("PZE.105068880", "PZE.106098900")

Qeff <- QTL_effect_GE(mppData = mppData_GE, trait = c('DMY_CIAM', 'DMY_TUM'),
                          Q.eff = 'par', QTL = Qpos)

Qeff

vincentgarin/mppGxE documentation built on June 25, 2022, 2:45 p.m.