Maury

Introduction

Maury is an R package that can be used to quantify relatedness of multiple samples from Next Generation Sequencing data(NGS).

Maury works by looking at genotypes at sites of common polymorphisms. Maury uses Maximum Likelihood Estimation(MLE) to infer the genotype of a sample at a particular locus by looking at the read depths of the reference and alternate alleles. Essentially there are three states for the genotypes(hom-ref, het or hom-alt) to choose from. Maury outputs the proportion of genotypes that are concordant between a pair of samples. .

A sample VCF with a recommended list of common polymorphisms using information from Pengelly et al. (A SNP profiling panel for sample tracking in whole-exome sequencing studies. http://www.ncbi.nlm.nih.gov/pubmed/24070238) is distributed with this package under inst/extdata/.

Maury can be used in a multitude of applications, for example identifying related samples within a cohort of individuals assumed to be unrelated. The proportion of shared genotypes will be proportional to the relatedness of the samples.

Example analysis

For a sample analysis using maury, please refer to https://github.com/gatoravi/maury/wiki

Install

devtools::install_github("gatoravi/maury")

Example Usage

library(maury)
bam1 <- system.file("extdata", 'ex1.bam',
    package = "maury", mustWork = TRUE)
bam2 <- system.file("extdata", 'ex1.bam',
    package = "maury", mustWork = TRUE)
vcf <- system.file("extdata", 'ex1.vcf',
    package = "maury", mustWork = TRUE)
maury("test_sample", vcf, bam1, bam2,
    min_rd = 0, min_mq = 0, min_bq = 0)