Metadata-Version: 2.1
Name: lisa2
Version: 2.2.4
Summary: Lisa: inferring transcriptional regulators through integrative modeling of public chromatin accessibility and ChIP-seq data. X. Shirley Liu Lab, 2020
Home-page: https://genomebiology.biomedcentral.com/articles/10.1186/s13059-020-1934-6
Author: Allen Lynch
Author-email: alynch@ds.dfci.harvard.edu
License: UNKNOWN
Description: 
        # About
        
        LISA is a statistical test for the influence of Transcription Factors on a set of genes. We leverage integrative modeling of public chromatin accessiblity and factor binding to 
        make predictions that go beyond simple co-expression analysis. The minimum you need to run LISA is a list of genes-of-interest, 
        but you can also supply your own epigenetic background. For more information, see Qin et al., 2020. 
        This implementation extends the original, running faster, reducing dependencies, and adding useful CLI functions for pipeline integration.
        
        # Documentation
        
        Please see Lisa's [github repo](https://github.com/liulab-dfci/lisa2) for source code and tutorials.
        
        # Installation
        
        ### Requirements
        
        * Mac or Linux OS
        * Python 3.6+
        * 15 GB of available storage space
        
        ### Installation
        
        LISA will install data into the virutal environment's "site_packages" directory, so ensure the env's location can store ~10GB.
        
        ### PyPI
        
        It is recommended to install lisa to a virtual environment:
        
            $ python3 -m venv .venvs/lisa_env
            $ source .venvs/lisa_env/bin/activate
        
        Install LISA to this virtual env using this command:
        
            (lisa_env) $ pip install lisa2
        
        ### Conda
        
        First, create a virtual environment:
        
            (base) $ conda create --name lisa_env
            (base) $ conda activate lisa_env
        
        Then install from Conda:
        
            (lisa_env) $ conda install -c liulab-dfci lisa2
        
        ### Dependencies
        
        * numpy
        * scipy
        * h5py
        * pyBigWig
        * scikit-learn
        
            
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6,<4
Description-Content-Type: text/markdown
