https://github.com/kullrich/vgwas

Variance Heterogeneity Genome-wide Association Study - Reimplementation
https://github.com/kullrich/vgwas

Last synced: 4 days ago
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Variance Heterogeneity Genome-wide Association Study - Reimplementation

• Host: GitHub
• URL: https://github.com/kullrich/vgwas
• Owner: kullrich
• Created: 2019-08-22T06:34:49.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2024-10-23T19:41:18.000Z (15 days ago)
• Last Synced: 2024-10-24T05:50:12.780Z (14 days ago)
• Language: HTML
• Size: 3.24 MB
• Stars: 0
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# vGWAS

[![Build Status](https://travis-ci.com/kullrich/vGWAS.svg?branch=master)](https://travis-ci.com/kullrich/vGWAS)

Variance Heterogeneity Genome-wide Association Study - Reimplementation

=========

This repository is a reimplementation from the original `vGWAS` R package from [Xia Shen](https://github.com/xiashen).

see the original publication

[Inheritance Beyond Plain Heritability: Variance-Controlling Genes in Arabidopsis thaliana](https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1002839)

some function has been added to directly perform GWAS on genotype data obtained

via [plink](https://www.cog-genomics.org/plink/)

the function `vGWASparallel` has been added to perform statistical tests in parallel

and work on genotype data encoded as sparse matrix

## Installation

### R specific installation prerequisites

```

install.packages("devtools")

install.packages("knitr")

install.packages("dglm")

install.packages("doParallel")

install.packages("foreach")

install.packages("genio")

install.packages("hglm")

install.packages("Matrix")

install.packages("onewaytests")

```

Install `vGWAS` package from [github](https://github.com/kullrich) using the [devtools](https://cran.r-project.org/web/packages/devtools/index.html) package.

```

library(devtools)

devtools::install_github("kullrich/vGWAS", build_vignettes = TRUE, dependencies = FALSE)

```

## Quick start

```

library(vGWAS)

data(pheno)

data(geno.sparse)

data(chr)

data(map)

vgwa <- vGWASparallel(

  phenotype = pheno,

  geno.matrix = geno.sparse,

  marker.map = map,

  chr.index = chr,

  geno.snp = "row"

)

plot(vgwa)

```

## Vignettes

These vignettes introduce `vGWAS`

- [01. vGWAS basic tutorial](https://github.com/kullrich/vGWAS/blob/master/vignettes/vGWAS.Rmd)

- [02. vGWAS plink tutorial](https://github.com/kullrich/vGWAS/blob/master/vignettes/vGWASsparse.Rmd)