garfield

This is the development version of garfield; for the stable release version, see garfield.

GWAS Analysis of Regulatory or Functional Information Enrichment with LD correction


Bioconductor version: Development (3.21)

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 (version "4.5") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("garfield")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

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

browseVignettes("garfield")
garfield Guide PDF
Reference Manual PDF
NEWS Text

Details

biocViews Annotation, FunctionalPrediction, GenomeAnnotation, Software, StatisticalMethod
Version 1.35.0
In Bioconductor since BioC 3.3 (R-3.3) (8.5 years)
License GPL-3
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Package Archives

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

Source Package garfield_1.35.0.tar.gz
Windows Binary (x86_64)
macOS Binary (x86_64)
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/garfield
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/garfield
Bioc Package Browser https://code.bioconductor.org/browse/garfield/
Package Short Url https://bioconductor.org/packages/garfield/
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