rarecover: RareCover statistical test

Description Usage Arguments Details Value References Examples

View source: R/rarecover.R

Description

Testing for rare variants with RareCover algorithm. This algorithm is similar to CMC, meaning that it follows its collapsing strategy, but uses greedy algorithm to find an optimized combination of variants in a loci for which its association signal is strongest.

Usage

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rarecover(table, maf=0.05, dif=0.5, perm=250)

Arguments

table

a numeric matrix with first column having disease status '0' or '1' and the rest columns codes the locus genotype as '0', '1', and '2'.

maf

numeric value indicating the minor allele frequency threshold for rare variants

dif

numeric value between 0 and 1 as a threshold for the decision criterion in the RareCover algorithm

perm

positive integer that defines the number of permutations. In permutation test, the distribution of the test statistic under the null hypothesis is obtained by calculating all possible values of the test statistic under rearrangements of the labels on the observed data points.

Details

....

Value

A list with the following elements:

rc.stat

RareCover statistic

perm.pval

permuted p-value

set

set of selected variants

args

descriptive information with number of controls, cases,variants, and permutations

name

name of the statistic

References

Bhatia G, Bansal V, Harismendy O, Schork NJ, Topol EJ, Frazer K, Bafna V (2010) A Covering Method for Detecting Genetic Associations between Rare Variants and Common Phenotypes. PLoS Computational Biology, 6(10): e1000954

Examples

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# Load the package

library(vartools)
?rarecover

casectrl.dat <- read.table(system.file("extdata","phengen.dat",package="vartools"), skip = 1)
rarecover.stat <- rarecover(casectrl.dat)
rarecover.stat

izhbannikov/vartools documentation built on May 17, 2017, 5:29 a.m.