Select genome

LocusCompare: Visualizing the colocalization of association summary statistics

Introduction

LocusCompare is a suite of tools and datasets to visualize the colocalization of summary statistics from pairs of association datasets (e.g. GWAS and eQTL). These tools and datasets include:

  • Colocalization statistics between more than 200 GWAS and 48 GTEx (version 7) tissues
  • Interactive LocusCompare plot to visualize a single locus
  • Bash script to download summary statistics of more than 200 GWAS

Documentations

For instructions please follow these links:

To download stand-alone version:

License

GPL v3 or later

Developers

  • Boxiang Liu (author, maintainer)
  • Mike Gloudemans (author, maintainer)
  • Abhiram Rao (author)
  • Stephen Montgomery (author)

Citation

If you use locuscompare, please cite the following paper: https://www.nature.com/articles/s41588-019-0404-0

Boxiang Liu, Michael J. Gloudemans, Abhiram S. Rao, Erik Ingelsson & Stephen B. Montgomery (2019) Abundant associations with gene expression complicate GWAS follow-up, Nature Genetics

Select Studies

Select GWAS

Select eQTL




Select Studies

Study 1

Select Published

Or Upload

Study 2

Select Published

Or Upload

Select a region (maximum window = 1Mb)

SNP

Or Gene

Or Coordinate




[INSTRUCTIONS] 1. Click on a point to select the corresponding SNP; 2. Drag and double-click on plots on the right-hand side to zoom in; 3. Double-click again to zoom out.


SNP information


                
Download options

                

                  
                  
                

                

                  
                  
                

                

                  
                  
                

                
                  
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LD SNPs

                  

                

                

                  

                

              

            

          

          

            

              

                
Downloading GWAS and QTL datasets

                
LocusCompare current hosts more than 200
							  GWAS datasets and 48 eQTL datasets.
							  We provide a convenient bash script for you to download 
							  these data.

                

                  Link to bash script: 
                  https://github.com/mikegloudemans/gwas-download
                

              

            

            

              

                
Acknowledgement

                
We are grateful to the individuals and organizations who have made 
							  their data publically available. Below is a list of studies 
							  we included in LocusCompare. If we missed a reference to your 
							  study, please email Boxiang Liu <bliu2@stanford.edu> or 
							  Mike Gloudemans <mgloud@stanford.edu>.

              

            

          

          

            

              

                

                  
Share your study

                  

                    Current GWAS datasets are distributed across various websites, making them difficult to find 
								  and download. LocusCompare provides a platform for sharing GWAS and QTL datasets. If you would like
								  to contribute your data to LocusCompare, please fill out the following form. 
								  Alternatively, you can email
                    Boxiang Liu
                    or
                    Mike Gloudemans
                    to add your study.
                    (* = mandatory)
                  

                

              

              

                

                  

                    
                    
                  

                  

                    
                    
                  

                  

                    
                    
                  

                  

                    
                    
                  

                  

                    
                    

                      
                      
                    

                    

                      

                    

                  

                

                

                  

                    
                    
                  

                  

                    
                    
                  

                  

                    
                    
                  

                  

                    
                    
                  

                  

                    
                    
                  

                

              

              

                

                  
                

              

            

            

              
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