Nothing
## ----setup, include = FALSE----------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## ----data----------------------------------------------------------------
library(mlmm.gwas)
data("mlmm.gwas.AD")
ls()
## ----matrixFormat, include=FALSE-----------------------------------------
# Change le formatage par d??faut des matrices
# On le met ici pour pas qu'il soit visible quand on fait ls() ci dessus
knit_print.matrix <- function(x, ...){
knitr::knit_print(as.data.frame(x), ...)
}
## ----floweringDateAD-----------------------------------------------------
head(floweringDateAD)
## ----X-------------------------------------------------------------------
Xa[1:5,1:5]
## ----K-------------------------------------------------------------------
##You can get K from X with the following command line
##We are not doing it here because the X matrix included in data("mlmm.gwas.AD")
##is a subset of a larger matrix.
#K.add = Xa %*% t(Xa)
K.add[1:5,1:5]
## ----mlmm----------------------------------------------------------------
res_mlmm = mlmm_allmodels(floweringDateAD, list(Xa), list(K.add))
## ----manhattan, fig.height=5, fig.width=5--------------------------------
manhattan.plot( res_mlmm )
## ----eBIC----------------------------------------------------------------
sel_XX = frommlmm_toebic(list(Xa), res_mlmm)
res_eBIC = eBIC_allmodels(floweringDateAD, sel_XX, list(K.add), ncol(Xa))
res_eBIC
## ----threshold-----------------------------------------------------------
res_threshold <- threshold_allmodels(threshold=NULL, res_mlmm)
## ----estimation----------------------------------------------------------
sel_XXclass = fromeBICtoEstimation(sel_XX, res_eBIC, res_threshold)
effects = Estimation_allmodels(floweringDateAD, sel_XXclass, list(K.add))
effects
## ----boxplot-------------------------------------------------------------
genotypes.boxplot(Xa, floweringDateAD, "SNP303", effects)
## ----completeExample, eval=FALSE-----------------------------------------
# library(mlmm.gwas)
# data("mlmm.gwas.AD")
#
# res_mlmm = mlmm_allmodels(floweringDateAD, list(Xa), list(K.add))
#
# manhattan.plot( res_mlmm )
#
# sel_XX = frommlmm_toebic(list(Xa), res_mlmm)
# res_eBIC = eBIC_allmodels(floweringDateAD, sel_XX, list(K.add), ncol(Xa))
#
# res_threshold <- threshold_allmodels(threshold=NULL, res_mlmm)
#
# sel_XXclass = fromeBICtoEstimation(sel_XX, res_eBIC, res_threshold)
# effects = Estimation_allmodels(floweringDateAD, sel_XXclass, list(K.add))
#
# genotypes.boxplot(Xa, floweringDateAD, "SNP303", effects)
## ----runEntirePipeline---------------------------------------------------
results = run_entire_gwas_pipeline(floweringDateAD, list(Xa), list(K.add), threshold=NULL)
names(results)
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