Metadata-Version: 1.0
Name: brie
Version: 0.2.2
Summary: BRIE: Bayesian regression for isoform estimate
Home-page: https://brie.readthedocs.io
Author: Yuanhua Huang
Author-email: yuanhua@ebi.ac.uk
License: Apache-2.0
Description-Content-Type: UNKNOWN
Description: |PyPI| |Docs| |Build Status|
        
        .. |PyPI| image:: https://img.shields.io/pypi/v/brie.svg
            :target: https://pypi.org/project/brie
        .. |Docs| image:: https://readthedocs.org/projects/brie/badge/?version=latest
           :target: https://brie.readthedocs.io
        .. |Build Status| image:: https://travis-ci.org/huangyh09/brie.svg?branch=master
           :target: https://travis-ci.org/huangyh09/brie
        
        
        BRIE: Bayesian Regression for Isoform Estimate
        ==============================================
        
        About BRIE
        ----------
        
        BRIE (Bayesian regression for isoform estimate) is a Bayesian method to 
        estimate isoform proportions from RNA-seq data. Currently, BRIE could take 
        sequence features to automatically learn informative prior of exon inclusion 
        ratio in  exon-skippiing events. This informative prior is very important when 
        limited data is available. In Bulk RNA-seq experiment, we could easily increase 
        the amplification to get more sequencing reads to improve the accuracy of 
        isoform estimate. However, in single cell RNA-seq (scRNA-seq) experiments, the 
        initial molecular is very limited, which always results some genes with very 
        low coverage or even drop-out. In scRNA-seq, the BRIE method, by integrating 
        informative prior, e.g. learned from sequence feature, could provide accurate 
        and reproducible estimates of splicing in single cells, as well as sensitive 
        differential analyses.
        
        
        BRIE provides following functions through command line:
        
        1. ``brie``: Estimate isoform proportions and FPKM, and calculate weights for 
        regulatory features.
        
        2. ``brie-diff``: Calculate Bayes factor of differential splicing between 
        multiple cells pair-wisely. 
        
        Quick Start
        -----------
        
        **Installation**: 
        
        - ``pip install brie``
        - or download this repository, and type ``python setup.py install``; 
        - add ``--user`` if you don't have root permission and you don't use Anaconda_.
        
        .. _Anaconda: https://www.continuum.io/anaconda-overview
        
        **Arguments**
        
        - Type command line ``brie -h``
        
        
        Detailed manual
        ---------------
        
        See the documentation_ on how to install, to use, to find the annotation data 
        etc.
        
        .. _documentation: https://brie.readthedocs.io
        
        
        References
        ----------
        
        Yuanhua Huang and Guido Sanguinetti. `BRIE: transcriptome-wide splicing quantification in single cells <https://genomebiology.biomedcentral.com/articles/10.1186/s13059-017-1248-5>`_. 
        \ **Genome Biology**\, 2017; 18(1):123.
        
Keywords: splicing isoform estimate,Bayesian regression,single cell RNA-seq,Markov chain Monte Carlo
Platform: UNKNOWN
