Compute weighted burden test

The function takes in a gene expression model (either legacy format or new isotwas_model format) and GWAS summary statistics and carries out the weighted burden Z-test for a trait.

Usage

burdenTest(
  mod,
  ld,
  gene,
  sumStats,
  chr = NULL,
  pos = NULL,
  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 = FALSE
)

Arguments

mod

Model for a given isoform. Can be: - A data.frame in legacy format with columns: Feature, SNP, Weight, R2, etc. - A single transcript model from isotwas_model$transcripts$<name> - An isotwas_model object (will use first transcript)

ld

matrix, ld reference matrix with SNP names as row/colnames

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

Value

data.frame with results for burden and permutation tests