Metadata-Version: 1.1
Name: calTADs
Version: 0.1.0-dev2
Summary: A hierarchical domain caller for Hi-C data based on a modified version of Directionality Index
Home-page: https://github.com/XiaoTaoWang/calTADs/
Author: XiaoTao Wang
Author-email: wangxiaotao868@163.com
License: UNKNOWN
Description: 
        Introduction
        ============
        3C-based techniques(5C, Hi-C) have revealed the existence of topologically
        associating domains(TADs), a pervasive sub-megabase scale structure of chromosome.
        TADs are contiguous regions in which loci interact much more frequently with
        each other than with loci out of the region. Visually, TADs appear as square
        blocks along the diagonal on a heatmap.
        
        There are various methods for TAD identification [1]_, [2]_. Most methods
        apply a two-step scheme: First, transform TAD or boundary signal into 1d
        profile using some statistic(e.g. Directionality Index, DI); Then, use the
        1d profile to identify potential boundaries and produce a set of discrete
        non-overlapping TADs. However, the organization of chromosome structure is
        always intricate and hierarchical. Phillips-Cremins JE et al. [3]_ utilized
        a modified DI of multiple scales subdivided TADs into smaller subtopologies (sub-TADs)
        using 5C data. Here, I extend their algorithm to the whole genome and develop
        this software.
        
        *calTADs* are tested on traditional [4]_ and *in-situ* [5]_ Hi-C data, both generating
        reasonable results.
        
        Installation
        ============
        Please check the file "INSTALL.rst" in the distribution.
        
        Links
        =====
        - `Repository <https://github.com/XiaoTaoWang/calTADs>`_
        - `PyPI <https://pypi.python.org/pypi/calTADs>`_
        
        Usage
        =====
        Open a terminal, type ``calTADs -h`` for help information.
        
        calTADs contains a process management system, so you can submit the same
        command repeatedly to utilize the parallel power as much as possible.
        
        Reference
        =========
        .. [1] Dixon JR, Selvaraj S, Yue F et al. Topological domains in
           mammalian genomes identified by analysis of chromatin interactions.
           Nature, 2012, 485: 376-380.
        
        .. [2] Sexton T, Yaffe E, Kenigsberg E et al. Three-dimensional folding
           and functional organization principles of the Drosophila genome.
           Cell, 2012, 148: 458-472.
        
        .. [3] Phillips-Cremins JE, Sauria ME, Sanyal A et al. Architectural protein
           subclasses shape 3D organization of genomes during lineage commitment.
           Cell, 2013, 153(6):1281-95.
        
        .. [4] Lieberman-Aiden E, van Berkum NL, Williams L et al. Comprehensive
           mapping of long-range interactions reveals folding principles of the
           human genome. Science, 2009, 326: 289-293.
        
        .. [5] Rao SS, Huntley MH, Durand NC. A 3D map of the human genome at
           kilobase resolution reveals principles of chromatin looping.
           Cell, 2014, 159(7):1665-80.
        
Keywords: Hi-C TAD DI directionality index topologically associating domain chromosome organization
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Operating System :: POSIX
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
