README.md

postgwas

Facilitates annotation of genes to SNPs using proximity or LD information, creates regional and manhattan plots and contains an interaction network analysis tool for GWAS result data. Special features cover subphenotype (intermediate phenotype) comparison and rare variant display.

Installation

Option 1: Install from CRAN (1 minute)

setRepositories(ind = 1:6)
install.packages("postgwas")

See also the CRAN package repository.

Option 2: Install binary manually (1 minute and Windows only)

setRepositories(ind = 1:6)
install.packages("https://github.com/merns/postgwas/releases/download/1.11-2/postgwas_1.11-2.zip", repos=NULL)

This will install the Windows binary package built by us.

Option 3: Install from GitHub (5 minutes)

  1. Install (if you haven't already) a working development environment:

    • Windows: Install Rtools.
    • Mac: Install Xcode.
    • Linux: Install a compiler for your distribution. For instance, for Ubuntu this would be sudo apt-get install r-base-dev. Further instructions can be found at CRAN.
  2. Install (if you haven't already) the devtools package via CRAN:

    install.packages(c("devtools", "rstudioapi"))
    
  3. Install postgwas from GitHub via devtools:

    setRepositories(ind = 1:6)
    devtools::install_github("postgwas", username="merns")
    

First steps

Start by loading the postgwas package and read the excellent documentation.

library(postgwas)
vignette(postgwas)

Contribution

You are welcome to contribute!

Just contact one of the Repo owners Marko Ernsting, Milan Hiersche or Frank Rühle.

Citation

If you use the package for research, please cite the following PlosOne publication:

Hiersche, M., Ruehle, F., & Stoll, M. (2013). Postgwas: Advanced GWAS Interpretation in R. PloS one, 8(8), e71775. doi:10.1371/journal.pone.0071775

Use the following BibTex entry or download citation information from here.

@article{10.1371/journal.pone.0071775,
    author = {Hiersche, , Milan AND Rühle, , Frank AND Stoll, , Monika},
    journal = {PLoS ONE},
    publisher = {Public Library of Science},
    title = {Postgwas: Advanced GWAS Interpretation in R},
    year = {2013},
    month = {08},
    volume = {8},
    url = {http://dx.doi.org/10.1371%2Fjournal.pone.0071775},
    pages = {e71775},
    abstract = {We present a comprehensive toolkit for post-processing, visualization and advanced analysis of GWAS results. In the spirit of comparable tools for gene-expression analysis, we attempt to unify and simplify several procedures that are essential for the interpretation of GWAS results. This includes the generation of advanced Manhattan and regional association plots including rare variant display as well as novel interaction network analysis tools for the investigation of systems-biology aspects. Our package supports virtually all model organisms and represents the first cohesive implementation of such tools for the popular language R. Previous software of that range is dispersed over a wide range of platforms and mostly not adaptable for custom work pipelines. We demonstrate the utility of this package by providing an example workflow on a publicly available dataset.},
    number = {8},
    doi = {10.1371/journal.pone.0071775}
}        


merns/postgwas documentation built on May 22, 2019, 6:53 p.m.