- Mac OS X, or UNIX operating system (Microsoft Windows is not supported)
- Java SE 6 (or higher)
- Python version 2.7 (Python version 3 or higher is not supported)
- PIP (used for install Python libraries)
sudo easy_install pip
- Python intervaltree library
sudo pip install intervaltree
- Pandas (version 0.15.2 or higher)
sudo pip install pandas
- PLINK version 1.9 (August 1 release or newer)
The following description explains how to download DEPICT, test run it on example files and how to run it on your GWAS summary statistics.
Download the compressed DEPICT version 1 rel194 files and unzip the archive to where you would like the DEPICT tool to live on your system. Note that you when using DEPICT can write your analysis files to a different folder. Be sure to that you meet all the dependencies described above. If you run DEPICT at the Broad Institute, see below section.
Test run DEPICT
The following steps outline how to test run DEPICT on LDL cholesterol GWAS summary statistics from Teslovich, Nature 2010. This example is available in both the 1000 Genomes Project pilot phase DEPICT version and the 1000 Genomes Project phase 3 DEPICT version.
plink_executableto where PLINK executable (version 1.9 or higher) is on our system (e.g.
- Run DEPICT on the LDL summary statistics
- Investigate the results (see the Wiki for a description of the output format).
- DEPICT loci
- Gene prioritization results
- Gene set enrichment results
- Tissue enrichment results
The following steps allow you to run DEPICT on your GWAS summary statistics. We advice you to run the above LDL cholesterol example before this point to make sure that you meet all the necessary dependencies to run DEPICT.
- Make sure that you use hg19 genomic SNP positions
- Make an 'analysis folder' in which your trait-specific DEPICT analysis will be stored
- Copy the template config file from
src/python/template.cfgto your analysis folder and give the config file a more meaningful name
- Edit your config file
analysis_pathto your analysis folder. This is the directory to which output files will be written
gwas_summary_statistics_fileto your GWAS summary statistics file. This file can be either in plain text or gzip format (i.e. having the .gz extension)
- Specify the GWAS association p value cutoff (
association_pvalue_cutoff). We recommend using
- Specify the label, which DEPICT uses to name all output files (
- Specify the name of the association p value column in your GWAS summary statistics file (
- Specify the name of the marker column (
marker_col_name). Format: chr:pos, ie. '6:2321'. If this column does not exist chr_col and pos_col will be used, then leave if empty
- Specify the name of the chromosome column (
chr_col_name). Leave empty if the above
- Specify the name of the position column (
pos_col_name). Leave empty if the above
marker_col_nameis set. Please make sure that your SNP positions used human genome build GRCh37 (hg19)
- Specify the separator used in the GWAS summary statistics file (
separator). Options are
plink_executableto where PLINK 1.9 executable (August 1 release or newer) is on your system (e.g.
- If you are using other genotype data than the data part of DEPICT then point
genotype_data_plink_prefixto where your PLINK binary format 1000 Genomes Project genotype files are on your system. Specify the entire path of the filenames except the extension
- Run DEPICT
<path to DEPICT>/src/python/depict.py <path to your config file>
- Investigate the results which have been written to your analysis folder. See the Wiki for details on the output format
- Associated loci in file ending with
- Gene prioritization results in file ending with
- Gene set enrichment results in file ending with
- Tissue enrichment results in file ending with
Run the LDL example
- Copy the example config file
/cvar/jhlab/tp/depict/example/ldl_teslovich_nature2010.cfgto your working directory and
change analysis_pathto that directory
- Run DEPICT using
qsub -e err -o out -cwd -l h_vmem=12g /cvar/jhlab/tp/depict/src/python/broad_run.sh python /cvar/jhlab/tp/depict/src/python/depict.py <your modified config file>.cfg
Run DEPICT on own GWAS
- Follow the above steps 1-4
- Run DEPICT using
use UGER qsub -e err -o out -cwd -l m_mem_free=2.5g -pe smp 6 /cvar/jhlab/tp/depict/src/python/broad_run.sh python /cvar/jhlab/tp/DEPICT/src/python/depict.py <your modified config file>.cfg
Be aware that DEPICT needs at least needs 14GB memory when if modify the memory used per slot/thread.
Please send the log file (ending with
_log.txt) with a brief description of the problem to Tune H Pers (email@example.com).
The overall version of DEPICT follows the DEPICT publications. The current version is
v1 from Pers, Nature Communications, 2015 and the release follows the number of commits of the DEPICT git repository (
git log --pretty=format:'' | wc -l). The latest 1000 Genomes Project pilot phase DEPICT version is
rel138, the latest 1000 Genomes Project phase 3 version is
How to cite
1000 Genomes Project, because DEPICT makes extensively use of their data.
Data used in these examples
1000 Genomes Consortium pilot release and phase 3 release data are used in DEPICT. Please remember to cite their paper in case you use our tool.