SKAT.SSD.All: SNP-set Kernel Association Test

Description

Iteratively carry out association tests with phenotypes and SNP sets in SSD file.

Usage

SKAT.SSD.All(SSD.INFO, obj, ..., obj.SNPWeight=NULL)
	
	SKATBinary.SSD.All(SSD.INFO, obj, ..., obj.SNPWeight=NULL)
	
	SKATBinary_Robust.SSD.All(SSD.INFO, obj, ...,obj.SNPWeight=NULL)
	
	SKAT_CommonRare.SSD.All(SSD.INFO, obj, ..., obj.SNPWeight=NULL)
	SKAT_CommonRare_Robust.SSD.All(SSD.INFO, obj, ..., obj.SNPWeight=NULL)

Value

results: dataframe that contains SetID, p-values (P.value), the number of markers in the SNP sets (N.Marker.All), and the number of markers to test for an association after excluding non-polymorphic or high missing rates markers (N.Marker.Test). The output dataframe from SKATBinary.SSD.All (and others) have more columns. For example, the outcome from SKATBinary.SSD.All have columns for the method to compute p-values and the minimum achievable p-values (MAP).
P.value.Resampling: the matrix that contains p-values of resampled phenotypes.
OUT.snp.mac: each element in the list is a vector of MAC of SNPs used in the test. The names are SNP-IDs.

Arguments

SSD.INFO: SSD_INFO object returned from Open_SSD.
obj: output object from SKAT_Null_Model.
...: further arguments to be passed to ``SKAT'' or ``SKATBinary''.
obj.SNPWeight: output object from Read_SNP_WeightFile (default=NULL). If NULL, the beta weight with the ``weights.beta'' parameter will be used.

Author

Seunggeun Lee

Details

Please see SKAT or SKATBinary for details.