Description

colocRedRibbon is a RedRibbon based colocalization of large genome-wide association studies (GWAS) and expression quantitative trait locus (eQTL) analyses. colocRedRibbon was developped to pinpoint variants associated both with increased risk for a disease and gene expression variation. The method uses novel pre-filtering steps, shortlisting variants before applying colocalization analysis.

Installation

This procedure has been tested on debian/ubuntu but should work on any linux distribution.

Directly from Github

In R, just run

devtools::install_github("antpiron/colocRedRibbon")

or for dev branch,

devtools::install_github("antpiron/colocRedRibbon", ref = "dev")

Documentation

A R vignette with fully reproducible examples is available here. You can also open it from R with

vignette("colocRedRibbon")

Short summary

library(colocRedRibbon)
data("th", package = "colocRedRibbon")

## th.dt is a data.frame containing
## 
##        rsid pval.GWAS n.GWAS eaf.GWAS   or.GWAS ea.GWAS nea.GWAS pval.eQTL       pos n.eQTL zscore.eQTL ea.eQTL nea.eQTL eaf.eQTL
##   rs1003483     0.350 231420    0.510 1.0063199       T        G   0.68710   2167543    404       0.403       T        G    0.510
##   rs1003484     0.640 231420    0.260 0.9965061       A        G   0.92180   2167618    404      -0.098       A        G    0.260
##   rs1003889     0.990 187126    0.011 0.9993002       T        G   0.58720   1970108    317       0.543       T        G    0.011
## ...

## Create a new column indicating the direction of GWAS and assign the logarithms of the odds ratio of GWAS
th.dt$dir.GWAS <- log(th.dt$or.GWAS)

## Construct a colocRedRibbon S3 object
rrc.dec <- RedRibbonColoc(th.dt, risk="a", effect=`<=`,
                          columns=c(id="rsid", position="pos", a.type="cc", a="pval.GWAS", b="pval.eQTL",
                                    a.n="n.GWAS", a.eaf="eaf.GWAS", a.dir="dir.GWAS", 
                                    b.n="n.eQTL", b.eaf="eaf.eQTL", b.dir="zscore.eQTL"))

The plots are generated with

ggRedRibbonColoc(rrc.dec, shortid = "TH")

Citation

Please cite our medXriv preprint and optionnaly, the RedRibbon Life Science Alliance publication,

Anthony Piron, Florian Szymczak, Lise Folon, Daniel J. M. Crouch, Theodora Papadopoulou, Maria Inês Alvelos, Maikel L. Colli, Xiaoyan Yi, Marcin Pekalski, Type 2 Diabetes Global Genomics Initiative, Matthieu Defrance, John A. Todd, Décio L. Eizirik, Josep M. Mercader, Miriam Cnop.
Identification of novel type 1 and type 2 diabetes genes by co-localization of human islet eQTL and GWAS variants with colocRedRibbon.
medRxiv 2024.10.19.24315808; doi: https://doi.org/10.1101/2024.10.19.24315808 

Anthony Piron, Florian Szymczak, Theodora Papadopoulou, Maria Inês Alvelos, Matthieu Defrance, Tom Lenaerts, Décio L Eizirik, Miriam Cnop.
RedRibbon: A new rank-rank hypergeometric overlap for gene and transcript expression signatures.
Life Science Alliance. 2023 Dec 8;7(2):e202302203. doi: 10.26508/lsa.202302203. PMID: 38081640; PMCID: PMC10709657.