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.
QTL_effect_GE(
mppData,
trait,
VCOV = "UN",
ref_par = NULL,
QTL = NULL,
maxIter = 100,
msMaxIter = 100
)Return:
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.
An object of class mppData.
Character vector specifying which traits (environments) should be used.
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'
Optional Character expression defining the parental
allele that will be used as reference for the parental model. Default = NULL
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.
maximum number of iterations for the lme optimization algorithm. Default = 100.
maximum number of iterations for the optimization step inside the lme optimization. Default = 100.
Vincent Garin
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.
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>.
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
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