Metadata-Version: 2.1
Name: scbase
Version: 0.1.1
Summary: **scBASE** is a python implementation of "soft" zero-and-one inflated model for estimating cellular allelic proportions from scRNA-Seq data
Home-page: https://github.com/churchill-lab/scBASE
Author: Kwangbom "KB" Choi, Ph.D.
Author-email: kb.choi@jax.org
License: MIT license
Keywords: scbase
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: Click (>=6.0)
Requires-Dist: pystan (>=2.17)
Requires-Dist: h5py (>=2.8)
Requires-Dist: pandas (>=0.23.4)
Requires-Dist: loompy (>=2.0.14)
Requires-Dist: future
Requires-Dist: six

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scBASE
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.. image:: https://img.shields.io/pypi/v/scbase.svg
        :target: https://pypi.python.org/pypi/scbase

.. image:: https://travis-ci.org/churchill-lab/scBASE.svg?branch=master
        :target: https://travis-ci.org/churchill-lab/scBASE

Allele-specific expression (ASE) in single-cell resolution can reveal stochastic and dynamic features of gene expression in greater detail. However, analyzing single-cell ASE poses unique analytical challenges due to the extremely low depth of sequencing coverage per cell. In addition, allelic proportions often form U-shaped or W-shaped distribution because of the frequent occurrence of random monoallelic bursts. We propose a new method, **scBASE**, a “soft” zero-and-one inflated model for cellular allelic proportions in which we tackle data sparsity and variability by harnessing information derived from cell's population context.

* Free software: MIT license
* Documentation: https://churchill-lab.github.io/scBASE/


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History
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0.1.0 (2018-08-02)
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* First release on PyPI.


