View source: R/Meta_Null_Model.R
Meta_Null_Model | R Documentation |
Compute model parameters and residuals under the null model (H0) of no associations. It can be used only when individual level data are available.
Meta_Null_Model(y.list, x.list, n.cohort, out_type="C", n.Resampling=0)
Meta_Null_Model_EmmaX(y.list, x.list, n.cohort, K.list=NULL, Kin.File.list=NULL)
y.list |
a list object for phenotypes. Each element should be a vector of phenotypes. If you have 3 cohorts, it should have 3 elements. |
x.list |
a list object for covariates. Each element should be a vector or a matrix of covariates. If there are 3 cohorts, it should have 3 elements. If there are no covariates to adjust for, the element should be "intercept". See the examples. |
n.cohort |
a numeric value of the number of cohort. |
out_type |
an indicator for the outcome type. "C" for continuous outcomes and "D" for dichotomous outcomes. |
n.Resampling |
internal use only. |
K.list |
a list object of the kinship matrices. If K.list=NULL, the function reads files in Kin.File.list to obtain kinship matrices. |
Kin.File.list |
a list object of emmax-kin output file names. |
It returns an object that has model parameters and residuals. The returned object will be used to run MetaSKAT_wZ.
Seunggeun Lee
data(Example)
attach(Example)
#############################################################
# Compute a p-value of the first gene
obj<-Meta_Null_Model(y.list, x.list, n.cohort=3, out_type="D")
MetaSKAT_wZ(Z.list[[1]], obj)$p.value
#############################################################
# If you want to use the intercept-only model for the 2nd cohort
x.list[[2]]<-"intercept"
obj<-Meta_Null_Model(y.list, x.list, n.cohort=3, out_type="D")
MetaSKAT_wZ(Z.list[[1]], obj)$p.value
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