Metadata-Version: 1.0
Name: diceseq
Version: 0.2.6
Summary: DICEseq: Dynamic Isoform spliCing Estimator via sequencing data
Home-page: http://diceseq.sourceforge.net
Author: Yuanhua Huang
Author-email: Y.Huang@ed.ac.uk
License: MIT
Description: ===============================================================
        DICEseq: Dynamic Isoform spliCing Estimator via sequencing data
        ===============================================================
        
        About DICEseq
        =============
        
        DICEseq (Dynamic Isoform spliCing Estimator via sequencing data) estimates the 
        dynamics of isoform proportions jointly from time series RNA-seq experiments. 
        DICEseq is a Bayesian method based on a mixture model whose mixing proportions 
        represent isoform ratios. It incorporates the correlations from the temporal 
        structure, by coupling the isoform proportions at different times through a 
        latent Gaussian process (GP).
        
        DICEseq provides following functions through command line:
        
        1. ``diceseq``: estimate the isoform proportions and FPKM for time series data 
           jointly, or for a single time point. 
        
        2. ``dice-count``: fetch reads counts for entile gene, or specific reads counts,
           e.g. junction reads, for genes with exact one intron. This is special design 
           mainly for yeast.
        
        3. ``dice-bias``: estimate parameters for sequencing bias, including fragment 
           length distribution, reads sequence and position bias parameter. The output 
           file can be directly used for bias correction in ``diceseq``.
        
        In addition, DICEseq package also provides interface of a set of functions and 
        attributes as an object-oriented python module. Therefore, you could use some 
        of the module e.g., ``SampleFile`` to visualize the samples in gzip file in a 
        Gaussian process way, or ``BiasFile`` to visualize the bias parameters. Also, 
        the ``gtf_utils`` provides a set of ways to load gtf file, choose the genes, or 
        customize the coordinates of exons and introns, add and remove of specific 
        transcripts.
        
        
        Quick Start
        ===========
        
        **Installation**: 
        
        - ``pip install diceseq``
        - or download this repository, and type ``python setup.py install``. 
        - You may need to add ``--user`` if you don't have the root permission and you 
          don't use Anaconda_.
        
        .. _Anaconda: https://www.continuum.io/anaconda-overview
        
        **Arguments**
        
        - Type command line ``diceseq -h``
        
        
        
        Detailed Manual
        ===============
        
        See the documentation_ on how to install, to use, to find the annotation data 
        etc.
        
        .. _documentation: http://diceseq.sourceforge.net
        
        
        References
        ===========
        
        Yuanhua Huang and Guido Sanguinetti. `Statistical modeling of isoform splicing 
        dynamics from RNA-seq time series data 
        <http://bioinformatics.oxfordjournals.org/content/32/19/2965.abstract>`_. \ **Bioinformatics**\, 2016, 32(19): 2965-2972.
        
Keywords: splicing isoform quantification,time series RNA-seq,Gaussian process,Markov chain Monte Carlo
Platform: UNKNOWN
