mppR (version 1.5.0)

QTL_effect_main_QEI: Main and QTL by environment interaction model

Description

The function estimate a QTL model where each parental QTL allelic effect is decomposed into a main effect and a QTL by environment effect (QEI). It allows the user to determine which parental allelic effects have a significant interaction with the environment.

Usage

QTL_effect_main_QEI(
  mppData,
  trait,
  env_id = NULL,
  ref_env = NULL,
  ref_par = NULL,
  VCOV = "UN",
  QTL = NULL,
  maxIter = 100,
  msMaxIter = 100
)

Value

Return:

List with one data.frame per QTL that contains the following elements:

1. To be filled

2. To be filled

3. Significance of the parent main effect expressed as the -log10(p-val)

4. Significance of the parent QTLxE effect expressed as the -log10(p-val)

Arguments

mppData

An object of class mppData.

trait

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

env_id

Character vector specifying the environment names. By default, E1, ... En

ref_env

Optional Character expression defining the environment that will be used as reference for the parental model. By default, the last environment is set as reference.

ref_par

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

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.

Author

Vincent Garin

Details

The function estimate the following model

\(y_{icj} = E_j + C_{c_j} + \sum_{q=1}^{n_{QTL}}{x_{i_{q}p}*(\alpha_{p} + \beta_{pj})} + GE_{ijc} + e_{ijc}\)

where the QTL effect is decomposed into \(\alpha_{p}\) that represent the main parental allelic effect across environments and \(\beta_{pj}\) which is the QEI effect. allelic effects must be interpreted as deviation with respect to the reference parent ('ref_par') in the reference environment ('ref_env'). By default the reference parent is the one with the highest allelic frequency (e.g. central parent in a NAM population).

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.

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

if (FALSE) {

data(mppData_GE)

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

Qeff <- QTL_effect_main_QEI(mppData = mppData_GE,
                            trait = c('DMY_CIAM', 'DMY_TUM', 'DMY_INRA_P', 'DMY_KWS'),
                            env_id = c('CIAM', 'TUM', 'INRA', 'KWS'),
                            QTL = Qpos)

Qeff

}