Metadata-Version: 1.1
Name: runHiC
Version: 0.1.5
Summary: A easy-to-use Hi-C processing software based on hiclib
Home-page: https://github.com/XiaoTaoWang/HiC_pipeline
Author: XiaoTao Wang
Author-email: wangxiaotao868@gmail.com
License: UNKNOWN
Description: Introduction
        ------------
        runHiC is a easy-to-use Hi-C processing software based on hiclib (https://bitbucket.org/mirnylab/hiclib) [1]_.
        Different from hiclib, which was born for flexibility, runHiC is a customized pipeline, and can be
        run from command line directly.
        
        Links
        ------
        - `Repository <https://github.com/XiaoTaoWang/HiC_pipeline>`_
        - `PyPI <https://pypi.python.org/pypi/runHiC>`_
        
        Installation
        -------------
        - Install required python packages:
        
        We recommend using `conda <http://conda.pydata.org/miniconda.html>`_, an excellent Python package and
        environment manager.
        
        Open a terminal and type::
        
            $ conda install numpy numexpr scipy matplotlib cython biopython h5py pysam pip
        
        Install bx-python and joblib using pip::
        
            $ pip install joblib bx-python
        
        Install mirnylib and hiclib from source code:
        
        Download `mirnylib <https://bitbucket.org/mirnylab/mirnylib>`_ and `hiclib <https://bitbucket.org/mirnylab/hiclib>`_,
        and run install_linux.py contained in the unpacked folder, respectively.
        
        .. note:: According to our experiences, do not install mirnylib and hiclib through pip!
        
        - Non-python library (or software) dependencies:
        
        Install samtools:
        
        Download `samtools <http://sourceforge.net/projects/samtools/files/>`_, unpack it, change to the extracted
        directory::
        
            $ make
        
        Make **samtools** accessible to the system. (Via environment variable *PATH*)
        
        Install Bowtie2:
        
        Download the `source code <http://sourceforge.net/projects/bowtie-bio/files/bowtie2/>`_, unzip it and
        add the path to the extracted directory to *PATH*.
        
        - Install runHiC:
        
        Use easy_install::
        
            $ conda install setuptools
            $ easy_install runHiC
        
        Design Concepts
        ---------------
        runHiC is able to perform the entire analysis from sequencing data to corrected HeatMaps.
        
        runHiC separate the whole process into 5 stages and you can begin and end at any stage using certain
        subcommands.
        
        All 6 subcommands are listed below:
        
        - *mapping*: Iteratively map pair-end sequencing reads to a supplied genome
        - *merge*: Merge alignment results corresponding to the same experiment together
        - *filtering*: Remove noises at the level of aligned read pairs and restriction fragments
        - *binning*: Bin filtered reads at certain resolution (original Heat Maps are generated)
        - *correcting*: Perform iterative corrections on the original Heat Maps
        - *pileup*: Streamline all 5 subcommands above from *mapping* to *correcting*.
        
        Preparation
        -----------
        Before running this program, you need to carry out several other things to improve performance:
        
        - Re-organize your directory arrangements:
        
        Although not required, we recommend creating a data root directory separate from the working
        directory.
        
        - Place genome and sequencing data under the data root directory
        
        Genome sequences should be stored chromosome by chromosome in FASTA format under a subfolder named
        after corresponding genome name. Sequencing read-pairs should be stored in SRA or FASTQ format under
        another subfolder (any valid name).
        
        - Construct a metadata file describing your sequencing data under the working directory
        
        Four columns are required: prefix of SRA file name, cell line name, biological replicate label, and
        restriction enzyme name. An example file is distributed along with this software, please check it.
        
        Usage
        -----
        Open a terminal, type ``runHiC -h`` and ``runHiC <subcommand> -h`` for help information.
        
        
        References
        ----------
        .. [1] Imakaev M, Fudenberg G, McCord RP et al. Iterative correction of Hi-C data
              reveals hallmarks ofchromosome organization. Nat Methods, 2012, 9: 999-1003.
        
Keywords: Hi-C HiC ICE
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Operating System :: POSIX
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
