QTL_effect_GE {mppR}

MPP GxE QTL genetic effects

Description

Estimate the QTL parental allelic effects within environment. The estimation is performed using an exact mixed model with function from R package nlme. The significance of the allele effect is assessed using a Wald test.

Usage

QTL_effect_GE(
  mppData,
  trait,
  VCOV = "UN",
  ref_par = NULL,
  QTL = NULL,
  maxIter = 100,
  msMaxIter = 100
)

Arguments

mppData

An object of class mppData.

trait

Character vector specifying which traits (environments) should be used.

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'

ref_par

Optional Character expression defining the parental allele that will be used as reference for the parental model. Default = NULL

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.

Details

The estimated model is the following:

\underline{y}_{icj} = E_{j} + C_{cj} + \sum_{q=1}^{n_{QTL}} x_{i_{q}p} * \beta_{pj} + \underline{GE}_{icj} + \underline{e}_{icj}

For further details see the vignette.

Value

Return:

Qeff

List of data.frame (one per QTL) containing the following information:

1. QTL genetic effects

2. Standard error of the QTL effects.

3. Wald statistics of the effects.

4. P-value of the test statistics.

5. Significance of the QTL effects.

Author(s)

Vincent Garin

References

Pinheiro J, Bates D, DebRoy S, Sarkar D, R Core Team (2021). nlme: Linear and Nonlinear Mixed Effects Models_. R package version 3.1-152, <URL: https://CRAN.R-project.org/package=nlme>.

Examples

data(mppData_GE)

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

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

Qeff