LAVA is a tool to conduct genome-wide, local genetic correlation analysis on multiple traits, using GWAS summary statistics as input.
The primary publication for LAVA (currently under submission) is:
Werme J, van der Sluis S, Posthuma D, de Leeuw C (2021). LAVA: An integrated framework for local genetic correlation analysis. BiorXiv preprint. doi: 10.1101/2020.12.31.424652 (link)
When using LAVA, please refer to this paper.
The current R-implementation for LAVA, as well as documentation and tutorial, can be found in the GitHub repository here.
For questions, comments, feedback and feature requests, contact Josefin Werme.
The genome partition file used for the primary LAVA publication can be found in the support_data folder on the GitHub repository linked above, and the code used to create the partitioning can be found here. This partioning was created using the 1,000 Genomes phase 3 reference data (European panel, build GRCh37/hg19).
Ready to use PLINK format data files for the 1,000 Genomes phase 3 reference data are linked below for different ancestries. Note that when analysing data from a non-European ancestry, a new genome partitioning will need to be created based on the reference data for that ancestry using the code linked above.
|East Asian||440 MB||Download|
|South Asian||521 MB||Download|
|Middle/South American||492 MB||Download|
GTEx v8 eQTL and sQTL input files