LGRF.SSD.OneSet_SetIndex: LGRF tests for a single region/gene using SSD format files

In LGRF: Set-Based Tests for Genetic Association in Longitudinal Studies

Description

Test the association between an outcome variable and one region/gene using SSD format files.

Usage

LGRF.SSD.OneSet_SetIndex(SSD.INFO, SetIndex, result.null, Gsub.id=NULL, interGXT=FALSE, 
similarity='GR', impute.method='fixed', MinP.compare=FALSE, ...)

Arguments

SSD.INFO	SSD format information file, output of function “Open_SSD". The sets are defined by this file.
SetIndex	Set index. From 1 to the total number of sets.
result.null	Output of function “null.LGRF".
Gsub.id	The subject id corresponding to the genotype matrix, an m dimensional vector. This is in order to match the phenotype and genotype matrix. The default is NULL, where the order is assumed to be matched with Y, X and time.
interGXT	Whether to incorperate the gene-time interaction effect. Incorperating this effect can improve power if there is any gene-time interaction, but has slight power loss otherwise. The default is FALSE. *Please note that the second column of time should be included as a covairate when interGXT is TRUE.
similarity	Choose the similarity measurement for the genetic variants. Can be either "GR" for genetic relationship or "IBS" for identity by state. The default is "GR" for better computational efficiency.
impute.method	Choose the imputation method when there is missing genotype. Can be "random", "fixed" or "bestguess". Given the estimated allele frequency, "random" simulates the genotype from binomial distribution; "fixed" uses the genotype expectation; "Best guess" uses the genotype with highest probability.
MinP.compare	Whether to compare with the GEE based minimum p-value (MinP) test. The default is FALSE. Please note that implementing the GEE based MinP test is time consuming.
...	Other options of the GEE based MinP test. Defined same as in function “test.MinP".

Value

p.value	p-value of the LGRF test.
n.marker	number of tested SNPs in the SNP set.

Examples

# * Since the Plink data files used here are hard to be included in a R package, 
# The usage is marked by "#" to pass the package check.

#library(LGRF)

##############################################

# Plink data files: File.Bed, File.Bim, File.Fam
# Files defining the sets: File.SetID, File.SSD, File.Info
# For longitudinal data, outcome and covariates are saved in a separate file: Y, time, X. 
# Null model was fitted using function null.LGRF.

# Create the MW File
# File.Bed<-"./example.bed"
# File.Bim<-"./example.bim"
# File.Fam<-"./example.fam"
# File.SetID<-"./example.SetID"
# File.SSD<-"./example.SSD"
# File.Info<-"./example.SSD.info"

# Generate SSD file
# To use binary ped files, you have to generate SSD file first.
# If you already have a SSD file, you do not need to call this function.
# Generate_SSD_SetID(File.Bed, File.Bim, File.Fam, File.SetID, File.SSD, File.Info)

# SSD.INFO<-Open_SSD(File.SSD, File.Info)
# Number of samples
# SSD.INFO$nSample
# Number of Sets
# SSD.INFO$nSets

## Fit the null model
# Y: outcomes, n by 1 matrix where n is the total number of observations
# X: covariates, n by p matrix
# time: describe longitudinal structure, n by 2 matrix
# result.null<-null.LGRF(Y,time,X=cbind(X,time[,2]))

# *Please note that the second column of time should be included as a covairate if
# the gene by time interaction effect will be incorperated. 

## Test a single region
# out_single<-LGRF.SSD.OneSet_SetIndex(SSD.INFO=SSD.INFO, SetIndex=1, 
# result.null=result.null, MinP.compare=F)

# Example result
# $p.value
# [1] 0.6284

# $n.marker
# [1] 94

## Test a single region, and compare with GEE based MinP test
# out_single<-LGRF.SSD.OneSet_SetIndex(SSD.INFO=SSD.INFO, SetIndex=1, 
# result.null=result.null,MinP.compare=T)

# $p.value
#       LGRF MinP
# [1,] 0.6284    1

# $n.marker
# [1] 94

LGRF documentation built on May 2, 2019, 10:59 a.m.