fromeBICtoEstimation {mlmm.gwas}

Helper function that create the selec_XXclass argument of the Estimation_allmodels function

Description

Function that create the selec_XXclass argument of the Estimation_allmodels function from the output of the eBIC_allmodels function or from the output of the threshold_allmodels function.

Usage

fromeBICtoEstimation(XX, res.eBIC, res.threshold)

Arguments

XX

A list of length one, two or three matrices depending on the model. Matrices are n by m matrix, where n=number of individuals, m=number of SNPs, with rownames(X)=individual names, and colnames(X)=SNP names.

- additive: a single matrix

- additive+dominance: two matrices

- female+male: two matrices with the female one first

- female+male+interaction: three matrices with the female first, the male then the interaction

res.eBIC

output of the eBIC_allmodels function

res.threshold

output of the threshold_allmodels function

See Also

eBIC_allmodels Estimation_allmodels

Examples

### Additive model ###
## Not run: 
data("mlmm.gwas.AD")

XX = list(Xa)
KK = list(K.add)

# GWAS
res_mlmm <- mlmm_allmodels(floweringDateAD, XX, KK)
manhattan.plot(res_mlmm)

# Model selection
sel_XX <- frommlmm_toebic(XX, res_mlmm)
res.eBIC <- eBIC_allmodels(floweringDateAD, sel_XX, KK, ncol(Xa))

# Effects estimations with the selected model
sel_XXclass <- fromeBICtoEstimation(sel_XX, res.eBIC)
eff.estimations <- Estimation_allmodels(floweringDateAD, sel_XXclass, KK)
genotypes.boxplot(Xa, floweringDateAD, effects = eff.estimations)

## End(Not run)

### Additive + dominance model
## Not run: 
data("mlmm.gwas.AD")

XX = list(Xa, Xd)
KK = list(K.add, K.dom)

# GWAS
res_mlmm <- mlmm_allmodels(floweringDateAD, XX, KK)
manhattan.plot(res_mlmm)

# Model selection
sel_XX <- frommlmm_toebic(XX, res_mlmm)
res.eBIC <- eBIC_allmodels(floweringDateAD, sel_XX, KK, ncol(Xa))
#the selected model is the null model

## End(Not run)


### Female+Male model
## Not run: 
data("mlmm.gwas.FMI")

XX = list(Xf, Xm)
KK = list(K.female, K.male)

# GWAS
res_mlmm <- mlmm_allmodels(floweringDateFMI, XX, KK, female = female, male = male)
manhattan.plot(res_mlmm)

# Model selection
sel_XX <- frommlmm_toebic(XX, res_mlmm)
res.eBIC <- eBIC_allmodels(floweringDateFMI, sel_XX, KK, ncol(Xf), female = female, male = male)
#the selected model is the null model

## End(Not run)



### Female+Male+Interaction model
## Not run: 
data("mlmm.gwas.FMI")

XX = list(Xf, Xm, Xfm)
KK = list(K.female, K.male, K.hybrid)

# GWAS
res_mlmm <- mlmm_allmodels(floweringDateFMI, XX, KK, female = female, male = male)
manhattan.plot(res_mlmm)

# Model selection
sel_XX <- frommlmm_toebic(XX, res_mlmm)
res.eBIC <- eBIC_allmodels(floweringDateFMI, sel_XX, KK, ncol(Xf), female = female, male = male)
#the selected model is the null model

## End(Not run)