Metadata-Version: 1.0
Name: diceseq
Version: 0.1.7
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
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        About DICEseq
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        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:
        
        1. Estimate the isoform proportions jointly. The prior is GPs followed by a softmax functions transformation.
        2. Estimate the isoform proportions separately. It is the same as MISO_, except prior.
        3. Calculate the Bayes factor to detect the differential dynamics of splicing profile.
        4. Get the total counts of each gene.
        5. Get the specific counts, e.g., junction reads, for genes with exactly one intron.
        6. Reads sequence and position bias correction and plot
        
        .. _MISO: http://genes.mit.edu/burgelab/miso/
        
        In addition to run the DICEseq functions from standard command line, DICEseq also provides interface of a set of functions and attributes as an object-oriented python module. Therefore, you could, for example customize the coordinates of exons and introns, add and remove of specific transcripts.
        
        More information
        ----------------
        
        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**\. (`under review`_)
        
        .. _under review: 
        
Keywords: splicing isoform quantification,time series RNA-seq,Gaussian process,Markov chain Monte Carlo
Platform: UNKNOWN
