README.md

In carltonyfakhry/geneticsCRE: geneticsCRE is an R package that performs genome-wide association study pathway analysis (GWASPA) to identify statistically significant associations between variants on gene regulatory pathways and a given phenotype

geneticsCRE

An R package that performs pathway-based genome-wide association study (PGWAS) to identify statistically significant associations between variants on gene regulatory pathways and a given phenotype. Unlike Genome-wide association study (GWAS), that seeks to assign statistical significance to associations of variations in single genes to a phenotype, PGWAS accumulates statistical power by examining rare variants along gene-gene interaction pathways. PGWAS uses prior causal information from gene regulatory interactions to infer statistically significant associations between causal pathways and a phenotype. Given phenotype data with case/control information, geneticsCRE computes PGWAS for all valid pathways as identified by the Homo Sapien STRINGdb causal network. Examples on usage are provided in the vignette.

Quickstart

geneticsCRE can be run from a Docker image:

docker run -it -v </path/to/workspace>:/work gcre/gcre:latest

The image is about 1GB in size, and provides a pre-configured Rcpp development environment. On startup, it will install the R package from GitHub - using build settings appropriate for the hardware - and then drop into a shell.

• /path/to/workspace is the host directory that contains any necessary data and scripts.
• If running on macOS/OSX, Docker for Mac (https://www.docker.com/docker-mac) should work better than the legacy "Docker Toolbox".
• More details, build scripts, and Dockerfiles can be found here: https://github.com/dbichko/gcre-ci
• Docker Hub organization: https://hub.docker.com/r/gcre/

It's possible to bypass the automatic installation by specifying a Docker run command (most likely a shell); the install can then be run manually:

docker run -it -v </path/to/workspace>:/work gcre/gcre:latest bash
docker@09caf52a75ef:~$ ./install

Installation

Before installing this package, make sure you have the latest versions of Rstudio, R, and the devtools package.

A recent version of Clang (https://clang.llvm.org/) is highly recommended. To configure the build environment, create ~/.R/Makevars:

CXX1X=clang++
CXX=clang++
CC=clang

CXX1XFLAGS=-O3 -march=native
CXXFLAGS=$(CXX1XFLAGS)

You can then install the R package using the following command:

devtools::install_github("carltonyfakhry/geneticsCRE", build_vignettes = TRUE, local = FALSE)

For an introduction to geneticsCRE and for an example on how to compute GWASPA over the publicly available network STRINGdb, please see the Vignette for this package using the following:

browseVignettes("geneticsCRE")

carltonyfakhry/geneticsCRE documentation built on May 13, 2019, 12:49 p.m.