DT_ige: Data to fit indirect genetic effects.

In sommer: Solving Mixed Model Equations in R

Data to fit indirect genetic effects.

Description

This dataset contains phenotpic data for 98 individuals where they are measured with the purpose of identifying the effect of the neighbour in a focal individual.

Usage

data("DT_ige")

Format

The format is: chr "DT_ige"

Source

This data was masked from a shared study.

References

Covarrubias-Pazaran G (2016) Genome assisted prediction of quantitative traits using the R package sommer. PLoS ONE 11(6): doi:10.1371/journal.pone.0156744

See Also

The core functions of the package mmer and mmec

Examples

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#### For CRAN time limitations most lines in the 
#### examples are silenced with one '#' mark, 
#### remove them and run the examples
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#### EXAMPLES
#### Different models with sommer
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data(DT_ige)
DT <- DT_ige
# # Indirect genetic effects model without covariance between DGE and IGE
# modIGE <- mmec(trait ~ block, dateWarning = FALSE,
#                random = ~ focal + neighbour,
#                rcov = ~ units, nIters=100,
#               data = DT)
# summary(modIGE)$varcomp
# pmonitor(modIGE)
# 
# # Indirect genetic effects model with covariance between DGE and IGE using relationship matrices
# modIGE <- mmec(trait ~ block, dateWarning = FALSE,
#                random = ~ covc( vsc(isc(focal)), vsc(isc(neighbour)) ),
#                rcov = ~ units, nIters=100,
#               data = DT)
# summary(modIGE)$varcomp
# pmonitor(modIGE)
# 
# # form relationship matrix
# Ai <- as( solve(A_ige + diag(1e-5, nrow(A_ige),nrow(A_ige) )), Class="dgCMatrix")
# # Indirect genetic effects model with covariance between DGE and IGE using relationship matrices
# modIGE <- mmec(trait ~ block, dateWarning = FALSE,
#                random = ~ covc( vsc(isc(focal), Gu=Ai), vsc(isc(neighbour), Gu=Ai) ),
#                rcov = ~ units, nIters=100,
#               data = DT)
# summary(modIGE)$varcomp
# pmonitor(modIGE)

sommer documentation built on Nov. 13, 2023, 9:05 a.m.