Metadata-Version: 1.1
Name: runHiC
Version: 0.6.2
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@163.com
License: UNKNOWN
Description: Introduction
        ============
        runHiC is a easy-to-use Hi-C processing software based on hiclib (https://bitbucket.org/mirnylab/hiclib)
        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
        ============
        Please check the file "INSTALL.rst" in the distribution.
        
        Design Concepts
        ===============
        runHiC is able to perform the entire analysis from sequencing data to corrected contact matrices. It
        separates the whole process into 4 stages(*mapping*, *filtering*, *binning*, *correcting*). You can
        begin and end at any stage using certain subcommands.
        
        7 subcommands are available:
        
        :mapping:        Iteratively map pair-end sequencing reads to a supplied genome
        :filtering:      Remove noises at the level of aligned read pairs and restriction fragments
        :binning:        Generate original contact matrices
        :correcting:     Perform iterative corrections on original contact matrices
        :tosparse:       Convert intra-chromosomal contact matrices to sparse ones
        :pileup:         Streamline all stages from *mapping* to *correcting*
        :quality:        Assess the quality of your experiments
        :visualize:      Plot the heatmap for given interval
        
        Preparation
        ===========
        Please refer to the **Sample** folder distributed with our source code.
        
        Directory Rearrangements
        ````````````````````````
        Although not required, I recommend creating a data root directory separate from the working
        directory.
        
        Data Placement
        ``````````````
        Both genome and sequencing data should be placed 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).
        
        Meta Data
        `````````
        Construct a meta data 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(Sample/working/datasets.tsv) is distributed along with this
        software, please check it.
        
        Usage
        =====
        Open a terminal, type ``runHiC -h`` and ``runHiC <subcommand> -h`` for help information.
        
Keywords: Hi-C HiC ICE Contact
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
