===============================================================
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
===========
**Environment and installation**:
DICEseq was initially developed in **Python 2** environment, hence best to be used
in Py2 environment. By using Anaconda_ platform, no matter Py2 or Py 3, it is
easy to set up a conda_ environment with Py2, for example by following commond:
.. code-block:: bash
conda create -n dicePy2 python=2.7 numpy==1.15.4 scipy==1.1.0 matplotlib==2.2.3 pysam==0.15.2
source activate dicePy2
Once you are in a Python 2 environment, there are usually two ways to isntall a
package:
- ``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 for that
environment.
.. _conda: https://conda.io/docs/user-guide/tasks/manage-environments.html
.. _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.
