rareGWAMA.cond.gene: conditional analysis for single variant association test;

In dajiangliu/rareGWAMA: Meta-Analysis of Gene-level Rare Variant Association Test in Whole Genome Datasets

Description

conditional analysis for single variant association test;

Usage

rareGWAMA.cond.gene(score.stat.file, imp.qual.file = NULL, vcf.ref.file,
  candidateVar.df, knownVar, alternative = "two.sided", ...)

Arguments

score.stat.file	the file names of score statistic files;
imp.qual.file	the file names of imputation quality;
vcf.ref.file	the file names of the reference panel file;
candidateVar.df	a data frame with pos being the position (pos) of the variants, and groupName being the groups that should be analyzed together;
knownVar	known variant;
alternative	The alternative hypothesis. Default is two.sided;
col.impqual	The column number for the imputation quality score;
impQual.lb	The lower bound for the imputation quality. Variants with imputaiton quality less than impQual.lb will be labelled as missing;
impQualWeight	Using imputation quality as weight
rmMultiAllelicSite	Default is TRUE. Multi-allelic sites will be removed from the analyses if set TRUE, and a variable posMulti will be output; The variant site with multiple alleles can be analyzed using rareGWAMA.single.multiAllele function;

Value

A list of analysis results;

dajiangliu/rareGWAMA documentation built on Sept. 13, 2019, 9:14 a.m.