Compute weighted burden test
burdenTest.Rd
The function takes in a gene expression model in MOSTWAS form and GWAS summary statistics and carries out the weighted burden Z-test for a trait
Usage
burdenTest(
mod,
ld,
gene,
sumStats,
chr,
pos,
a1,
a2,
a1_mod = "ALT",
a2_mod = "REF",
snpName = "SNP",
Z = NULL,
beta = NULL,
se = NULL,
featureName = "Feature",
R2cutoff = 0.01,
alpha = 2.5e-06,
nperms = 1000,
usePos = F
)
Arguments
- mod
data.frame, model for a given isoform
- ld
matrix, ld reference matrix
- gene
character, gene name
- sumStats
data frame, GWAS summary statistics
- chr
character, colnames in sumStats that keeps the chromosome
- pos
character, colnames in sumStats that keeps the position
- a1
character, colnames in sumStats that keeps the ALT allele
- a2
character, colnames in sumStats that keeps the REF allele
- a1_mod
character, colnames in model that keeps the ALT allele
- a2_mod
character, colnames in model that keeps the REF allele
- snpName
character, colnames in sumStats that keeps the SNP id
- Z
character, colnames in sumStats that keeps the Z score
- beta
character, colnames in sumStats that keeps the effect size
- se
character, colnames in sumStats that keeps the standard error
- featureName
character, colname in model that keeps the feature name
- R2cutoff
numeric, predictive R2 cutoff
- alpha
numeric, P-value threshold for permutation testing
- nperms
numeric, number of permutations
- usePos
logical, use SNP positions vs. SNP ids