Metadata-Version: 2.1
Name: CountESS
Version: 0.0.1
Summary: Analysis program for calculating variant scores from deep mutational scanning data.
Home-page: https://github.com/countess-project/countess
Author: Alan F Rubin
Author-email: alan.rubin@wehi.edu.au
License: UNKNOWN
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
Requires-Dist: numpy (>=1.10.4)
Requires-Dist: scipy (>=0.16.0)
Requires-Dist: pandas (>=0.18.0)
Requires-Dist: statsmodels (>=0.6.1)
Requires-Dist: matplotlib (>=1.4.3)
Requires-Dist: pyyaml (>=3.12)
Requires-Dist: sphinx-rtd-theme
Requires-Dist: sphinx (>=1.5.6)
Requires-Dist: tables (>=3.2.0)
Requires-Dist: dask[dataframe]
Requires-Dist: fastparquet

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CountESS
========

CountESS (Count-based Experiment Scoring and Statistics) is a general software tool for processing, analyzing, and visualizing data from high-throughput functional genomics experiments based on count data, such as deep mutational scanning.

This project extends previous work on Enrich2 by moving from Python 2.7 to Python 3.6+ and add adding new features to improve performance and enable analysis of new types of data.

Questions?
----------

Please use the [GitHub Issue Tracker](https://github.com/VariantEffect/CountESS/issues) to file bug reports or request features. 

CountESS is maintained by [Alan F Rubin](mailto:alan.rubin@wehi.edu.au).


