CAVIAR (CAusal Variants Identication in Associated Regions):

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a statistical framework that quantifies the probability of each variant to be causal while allowing with arbitrary number of causal variants.

original publications can be found here for eCAVIAR and here for CAVIAR.

Developed at the ZarLab at UCLA

More information on CAVIAR and eCAVIAR can be found on the CAVIAR website

information on running CAVIAR and eCAVIAR:

to install this repository --

git clone https://github.com/fhormoz/caviar.git

CAVIAR usage

./CAVIAR [options] 
Options:
-h, --help                  show this help message and exit 
-o OUTFILE, --out=OUTFILE   specify the output file
-l LDFILE, --ld_file=LDFILE the ld input file
-z ZFILE, --z_file=ZFILE    the z-score and rsID files
-r RHO, --rho-prob=RHO      set $pho$ probability 
-c causal           set the maximum number of causal SNPs
-f 1                to out the probaility of different number of causal SNP

eCAVIAR usage

Usage: ./eCAVIAR [options]

Options:
-h, --help                      show this help message and exit
-o OUTFILE, --out=OUTFILE       specify the output file
-l LDFILE, --ld_file=LDFILE     the GWAS ld input file
-l LDFILE, --ld_file=LDFILE     the eQTL ld input file
-z ZFILE, --z_file=ZFILE        the GWAS z-score and rsID files
-z ZFILE, --z_file=ZFILE        the eQTL z-score and rsID files
-r RHO, --rho-prob=RHO          set $pho$ probability
-c causal                       set the maximum number of causal SNPs
-f 1                            to out the probaility of different number of causal SNP

Output

OUTFILE_1_set - causal SNP in GWAS

OUTFILE_2_set - causal SNP in eQTL

OUTFILE_1_post - Causal posterior probability for each SNP in GWAS

OUTFILE_2_post - Causal posterior probability for each SNP in eQTL

OUTFILE_col - The Colocalization posterior probability (CLPP) for each SNP.

Debugging

CAVIAR is written in C++ and must be compiled before running. If you are encountering errors in running CAVIAR or eCAVIAR try these steps:

1. check if you have the GNU scientific library installed
   • for macOS this can be done using the homebrew package manager- brew install gsl
2. Next, in the caviar/CAVIAR C++ repository type make clean
3. make
4. chmod +x eCAVIAR may also be helpful CAVIAR should be able to run using these parameters

Other helpful hints - if running eCAVIAR make sure your LD files have the same SNPs, works best for low to medium LD other related code developed by UCSF students here

CAVIAR is offered under the GNU Affero GPL (https://www.gnu.org/licenses/why-affero-gpl.html).