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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