threshold_allmodels: Select significant marker thanks to a p-value threshold

In mlmm.gwas: Pipeline for GWAS Using MLMM

Description

Select significant marker at each mlmm step according to a threshold.

Usage

threshold_allmodels(threshold=NULL, res_mlmm)

Arguments

threshold	a value to declare the significant p value. The default value is Bonferroni 0.05
res_mlmm	a list of p-value for each mlmm step. Use helper function mlmm_allmodels to get this argument.

Value

A matrix with a line for significant SNP at each mlmm step (according to the defined threshold) and 3 columns : SNP, p-value, step

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 and Marker selection
sel_XX <- frommlmm_toebic(XX, res_mlmm)
res.eBIC <- eBIC_allmodels(floweringDateAD, sel_XX, KK, ncol(Xa))
res.threshold <- threshold_allmodels(threshold, res_mlmm)

# Effects estimations with the selected model
sel_XXclass <- fromeBICtoEstimation(sel_XX, res.eBIC, res.threshold)
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)

# Marker selection
res.threshold <- threshold_allmodels(threshold, res_mlmm)

## 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)

# Marker selection
res.threshold <- threshold_allmodels(threshold, res_mlmm)

## 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)

# Marker selection
res.threshold <- threshold_allmodels(threshold, res_mlmm)

## End(Not run)

mlmm.gwas documentation built on Aug. 5, 2019, 5:12 p.m.