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Colocalization

Co-localization analysis between reference GWAS and eQTL summary statistics

Sourya Bhattacharyya

La Jolla Institute for Immunology, La Jolla, CA 92037, USA


Implements colocalization between the reference GWAS summary statistics and input eQTL file.

Performs colocalization using the R package coloc (https://chr1swallace.github.io/coloc/index.html)

We use the coloc.abf() routine from the coloc package to perform the colocalization.

Prerequisites

  1. Install the following R libraries: coloc, data.table, stringr, snpStats, dplyr, yaml

Running the script

First edit the configuration file (configfile.yaml).

Check individual parameters related to both GWAS and eQTL summary statistics.

..Note.. Parameters marked as mandatory need to be provided.

..Note.. Allele frequency (AF) information need to be provided, either for the GWAS or for the eQTL data.

Once the configuration file is edited, run the script Colocalization_Analysis_GWAS_Script.sh. It will invoke the colocalization along with the corresponding configuration file.

Output

With respect to the specified output directory (parameter OutDir), check the following two files:

  1. FINAL_Summary_Coloc_Gene_SNP_Pairs.bed

Lists colocalized variants along with the GWAS and eQTL statistics, one per GWAS loci.

(By GWAS loci, we mean +/- 500 Kb from the significant GWAS SNPs)

  1. FINAL_Summary_Coloc_Gene_SNP_Pairs_95pct_credible_set.bed

For each GWAS loci, we list not only the top colocalized variant but also all variants within the 95% credible causal set.

Motivated by the latest release of coloc, and described here: https://chr1swallace.github.io/coloc/articles/a03_enumeration.html

Contact

For any queries, please create an issue and we'll respond. Otherwise, please e-mail

Sourya Bhattacharyya: [email protected]

Ferhat Ay: [email protected]

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