To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("http://bioc.ism.ac.jp/biocLite.R")
biocLite("garfield")

In most cases, you don't need to download the package archive at all.

garfield

 

   

GWAS Analysis of Regulatory or Functional Information Enrichment with LD correction

Bioconductor version: Release (3.5)

GARFIELD is a non-parametric functional enrichment analysis approach described in the paper GARFIELD: GWAS analysis of regulatory or functional information enrichment with LD correction. Briefly, it is a method that leverages GWAS findings with regulatory or functional annotations (primarily from ENCODE and Roadmap epigenomics data) to find features relevant to a phenotype of interest. It performs greedy pruning of GWAS SNPs (LD r2 > 0.1) and then annotates them based on functional information overlap. Next, it quantifies Fold Enrichment (FE) at various GWAS significance cutoffs and assesses them by permutation testing, while matching for minor allele frequency, distance to nearest transcription start site and number of LD proxies (r2 > 0.8).

Author: Sandro Morganella <sm22 at sanger.ac.uk>

Maintainer: Valentina Iotchkova <vi1 at sanger.ac.uk>

Citation (from within R, enter citation("garfield")):

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("http://bioc.ism.ac.jp/biocLite.R")
biocLite("garfield")

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("garfield")

 

PDF garfield Guide
PDF   Reference Manual
Text   NEWS

Details

biocViews Annotation, FunctionalPrediction, GenomeAnnotation, Software, StatisticalMethod
Version 1.4.0
In Bioconductor since BioC 3.3 (R-3.3) (1 year)
License GPL-3
Depends
Imports
LinkingTo
Suggests knitr
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Package Source garfield_1.4.0.tar.gz
Windows Binary garfield_1.4.0.zip (32- & 64-bit)
Mac OS X 10.11 (El Capitan) garfield_1.4.0.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/garfield/tree/release-3.5
Package Short Url http://bioconductor.org/packages/garfield/
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