Metadata-Version: 2.1
Name: pyfocus
Version: 0.4.1
Summary: Fine-map transcriptome-wide association studies
Home-page: https://github.com/bogdanlab/focus
Author: Nicholas Mancuso, Ruth Johnson
Author-email: nicholas.mancuso@med.usc.com, ruthjohnson@ucla.com
License: UNKNOWN
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.
        
        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](https://github.com/bogdanlab/focus/wiki) for more details on how to use focus and links to database files.
        
        Notes
        -----
        Version 0.4: Added FUSION import support.
        
        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:
        
        1. Association between predicted expression and complex trait/disease [FUSION](https://github.com/gusevlab/fusion_twas) and [PrediXcan](https://github.com/hakyimlab/PrediXcan)
        2. Estimating local heritability or genetic correlation [HESS](https://github.com/huwenboshi/hess)
        3. Estimating genome-wide heritability or genetic correlation [UNITY](https://github.com/bogdanlab/UNITY)
        4. Fine-mapping using summary-data [PAINTOR](https://github.com/gkichaev/PAINTOR_V3.0)
        5. Imputing summary statistics using LD [FIZI](https://github.com/bogdanlab/fizi)
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
