Fine-map transcriptome-wide association studies
Project description
FOCUS
FOCUS (Fine-mapping Of CaUsal gene Sets) is software to fine-map transcriptome-wide association study statistics at genomic risk regions. The software takes as input summary GWAS data along with eQTL weights and outputs a credible set of genes to explain observed genomic risk.
This is an initial draft of the README and extensive documentation is coming soon.
Installing
The easiest way to install is with pip:
pip install pyfocus --user
Check that FOCUS was installed by typing
focus --help
If that did not work, and pip install pyfocus --user
was specified, please check that your local user path is included in
$PATH
environment variable. --user
location and can be appended to $PATH
by executing
export PATH=`python -m site --user-base`/bin/:$PATH
which can be saved in ~/.bashrc
or ~/.bash_profile
. To reload the environment type source ~/.bashrc
or ~/source .bash_profile
depending where you entered it.
Alternatively you can download the latest repo and then use setuptools:
git clone https://github.com/bogdanlab/focus.git
cd focus
python setup.py install
*We currently only support Python3.6+. A conda-forge recipe that should simplify installation is currently underway.
Example
Here is an example of how to perform LDL fine-mapping while prioritizing predictive models from adipose tissues:
focus finemap LDL_2010.clean.sumstats.gz 1000G.EUR.QC.1 gtex_v7.db --chr 1 --tissue adipose --out LDL_2010.chr1
This command will scan LDL_2010.clean.sumstats.gz
for risk regions and then perform TWAS+fine-mapping using LD estimated from plink-formatted 1000G.EUR.QC.1
and eQTL weights from gtex_v7.db
.
Please see the wiki for more details on how to use focus.
Notes
Version 0.3: Initial release. More to come soon.
Software and support
If you have any questions or comments please contact nmancuso@mednet.ucla.edu
For performing various inferences using summary data from large-scale GWASs please find the following useful software:
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