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        "author": "Kwangbom \"KB\" Choi, Ph.D.",
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            "Development Status :: 4 - Beta",
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            "Programming Language :: Python :: 3",
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        "description": "======\nscBASE\n======\n\n\n.. image:: https://img.shields.io/pypi/v/scbase.svg\n        :target: https://pypi.python.org/pypi/scbase\n\n.. image:: https://travis-ci.org/churchill-lab/scBASE.svg?branch=master\n        :target: https://travis-ci.org/churchill-lab/scBASE\n\nAllele-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 \u201csoft\u201d 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.\n\n* Free software: MIT license\n* Documentation: https://churchill-lab.github.io/scBASE/\n\n\n=======\nHistory\n=======\n\n0.1.0 (2018-08-02)\n------------------\n\n* First release on PyPI.\n\n\n",
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        "summary": "**scBASE** is a python implementation of \"soft\" zero-and-one inflated model for estimating cellular allelic proportions from scRNA-Seq data",
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