burden.weighted.matrix: Score matrix for burden tests

In Ravages: Rare Variant Analysis and Genetic Simulations

Score matrix for burden tests

Description

Computes the score matrix for burden tests based on variants' weights

Usage

burden.weighted.matrix(x, weights, genomic.region = x@snps$genomic.region)

Arguments

x	A bed.matrix
weights	A vector containing the weight of each variant
genomic.region	A factorcontaining the genomic region of each variant

Details

For variant i and individual j, the genetic score will be computed as weight of variant i * number of minor alleles for individual j. This function returns a weighted score of rare alleles in the genomic region: if the reference allele is rare, it will be counted in the score instead of the atlernative allele.

Value

A matrix containing the computed genetic score with one row per individual and one column per genomic.region.

See Also

CAST, WSS, burden.mlogit

Examples

#Import data in a bed matrix
x <- read.bed.matrix( system.file("extdata", "LCT.EUR.b37.bed", package="Ravages") )

#Group variants within known genes
x <- set.genomic.region(x)

#Filter of rare variants: only non-monomorphic variants with
#a MAF lower than 2.5%
#keeping only genomic regions with at least 200 SNP
x1 <- filter.rare.variants(x, filter = "whole", maf.threshold = 0.025, min.nb.snps = 200)

#Compute burden score with weights = 1-maf
score.burden <- burden.weighted.matrix(x1, weights=1-x1@snps$maf)

Ravages documentation built on Feb. 27, 2026, 5:08 p.m.