MetaSKAT_MSSD_OneSet: Meta analysis SKAT with summary data from each study cohort.
In MetaSKAT: Meta Analysis for SNP-Set (Sequence) Kernel Association Test

View source: R/Meta_SKAT.R

MetaSKAT_MSSD_OneSet

R Documentation

Meta analysis SKAT with summary data from each study cohort.

Description

Meta analysis SKAT with Meta SSD (MSSD) and Info (MInfo) files. MetaSKAT_MSSD_OneSet computes a p-value for a given set, and MetaSKAT_MSSD_ALL computes p-values for all sets.

Usage


MetaSKAT_MSSD_OneSet(Cohort.Info, SetID, combined.weight=TRUE, weights.beta=c(1,25),
method="davies", r.corr=0, is.separate = FALSE, Group_Idx=NULL, MAF.cutoff=1, 
missing_cutoff=0.15)

MetaSKAT_MSSD_ALL(Cohort.Info, ...)

Arguments

`Cohort.Info`	output object from Open_MSSD_File_2Read.
`SetID`	a character value of set id to test.
`combined.weight`	a logical value (default=TRUE) for a type of weighting. See MetaSKAT_wZ page for details.
`weights.beta`	a numeric vector of parameters for the beta weights (default=c(1,25))
`method`	a method to compute a p-value (default= "davies"). See MetaSKAT_wZ page for details.
`r.corr`	the `\rho` parameter for the compound symmetric correlation structure kernels (default= 0). See MetaSKAT_wZ page for details.
`is.separate`	a logical value (default=FALSE) for homogeneous(=FALSE) or heterogeneous(=TRUE) genetic effects of a SNP set across studies. See MetaSKAT_wZ page for details.
`Group_Idx`	a vector of group indicator (default=NULL). See MetaSKAT_wZ page for details.
`MAF.cutoff`	a cutoff of the MAFs of SNPs (default=1). Any SNPs with MAFs > MAF.cutoff will be excluded from the analysis.
`missing_cutoff`	a cutoff of the missing rates of SNPs (default=0.15). See MetaSKAT_wZ page for details.
`...`	the same parameters of MetaSKAT_MSSD_OneSet after SetID.

Details

Please see MetaSKAT_wZ for details.

Value

MetaSKAT_MSSD_OneSet and MetaSKAT_wZ return the same object. See MetaSKAT_wZ for details. MetaSKAT_MSSD_ALL returns a dataframe with SetIDs (first column) and p-values (second column).

Author(s)

Seunggeun Lee

References

Lee, S., Teslovich, T., Boehnke, M., Lin, X. (2013) General framework for meta-analysis of rare variants in sequencing association studies. American Journal of Human Genetics, 93, 42-53.

MetaSKAT documentation built on Oct. 8, 2024, 5:07 p.m.