sumFREGAT (version 1.0.0)

BT: Family Burden Test

Description

Burden test on summary statistics

Usage

BT(scoreFile, geneFile, regions, cor.path = "", annoType = "",
beta.par = c(1, 25), weights.function = ifelse(maf > 0,
dbeta(maf, beta.par[1], beta.par[2]), 0), write.file = FALSE)

Arguments

scoreFile

name of data file generated by prep.score.files().

geneFile

name of a text file listing genes in refFlat format. If not set, hg19 file will be used (see Examples below).

regions

character vector of gene names to be analysed. If not set, function will attempt to analyse all genes listed in geneFile.

cor.path

path to a folder with correlation files (one file per each gene to be analysed). Names of correlation files should be constructed as "geneName.cor" (e.g. "ABCG1.cor", "ADAMTS1.cor", etc.) Each file should contain a square matrix with correlation coefficients (r) between genetic variants of a gene. An example of correlation file format: "snpname1" "snpname2" "snpname3" ... "snpname1" 1 0.018 -0.003 ... "snpname2" 0.018 1 0.081 ... "snpname3" -0.003 0.081 1 ... ... One way to generate such file from original genotypes is: write.table(cor(g), file = paste0(geneName, ".cor")) where g is a genotype matrix (nsample x nvariants) for a given gene with genotypes coded as 0, 1, 2 (exactly the same coding that was used to generate betas).

annoType

for files annotated with the seqminer package, a character (or character vector) indicating annotation types to be used (e.g. "Nonsynonymous", "Start_Loss", "Stop_loss", "Essential_Splice_Site")

beta.par

two positive numeric shape parameters in the beta distribution to assign weights for each genetic variant as a function of MAF in the default weights function (see Details). Default = c(1, 25).

weights.function

a function of minor allele frequency (MAF) to assign weights for each genetic variant. By default, the weights will be calculated using the beta distribution (see Details).

write.file

output file name. If specified, output (as it proceeds) will be written to the file.

Value

A data frame containing P values, estimates of betas and their s.e., numbers of variants and filtered variants for each of analyzed regions.

Details

Burden test (collapsing technique) suggests that the effects of causal genetic variants within a region have the same direction. If this is not the case, other regional tests (SKAT and FLM) are shown to have higher power compared to burden test [Svishcheva, et al., 2015]. By default, BT assigns weights calculated using the beta distribution. Given the shape parameters of the beta function, beta.par = c(a, b), the weights are defined using probability density function of the beta distribution:

\(W_{i}=(B(a,b))^{^{-1}}MAF_{i}^{a-1}(1-MAF_{i})^{b-1} \),

where \(MAF_{i}\) is a minor allelic frequency for the \(i^{th}\) genetic variant in region, which is estimated from genotypes, and \(B(a,b)\) is the beta function. beta.par = c(1, 1) corresponds to the unweighted burden test.

References

Svishcheva G.R., Belonogova N.M. and Axenovich T.I. (2015) Region-based association test for familial data under functional linear models. PLoS ONE 10(6): e0128999.

Examples

# NOT RUN {
## Run BT with example files:
VCFfileName <- system.file("testfiles/CFH.scores.anno.vcf.gz",
	package = "sumFREGAT")
cor.path <- system.file("testfiles/", package = "sumFREGAT")
out <- BT(VCFfileName, region = 'CFH', cor.path = cor.path)

# }