Metadata-Version: 1.1
Name: TADLib
Version: 0.1.1
Summary: A Library to Explore Chromatin Interaction Patterns for Topologically Associating Domains
Home-page: https://github.com/XiaoTaoWang/TADLib/
Author: XiaoTao Wang
Author-email: wangxiaotao868@gmail.com
License: UNKNOWN
Description: Introduction
        ------------
        Chromosome conformation capture (3C) derived techniques, especially Hi-C,
        have revealed that topologically associating domain (TAD) is a structural
        basis for both chromatin organization and regulation in three-dimensional
        (3D) space. To systematically investigate the relationship between structure
        and function, it is important to develop a quantitative parameter to measure
        the structural characteristics of TAD. TADLib is such a package to explore
        the chromatin interaction pattern of TAD.
        
        Inspired by the observation that there exist great differences in chromatin
        interaction pattern and gene expression level among TADs, a chromatin interaction
        feature is developed to capture the aggregation degree of long-range chromatin
        interactions. Application to human and mouse cell lines shows that there
        exist heterogeneous structures among TADs and the structural rearrangement across
        cell lines is significantly associated with transcription activity remodeling.
        
        TADLib package is written in Python and provides a four-step pipeline:
        
        - Identifying TAD from Hi-C data (optional)
        - Selecting long-range chromatin interactions in each TAD
        - Finding the aggregation patterns of selected interactions
        - Calculating chromatin interaction feature of TAD
        
        Installation
        ------------
        Please check the file "INSTALL.rst" in the distribution.
        
        Links
        -----
        - `Detailed Documentation <http://pythonhosted.org//TADLib/>`_
        - `Repository <https://github.com/XiaoTaoWang/TADLib>`_ (At GitHub)
        - `PyPI <https://pypi.python.org/pypi/TADLib>`_ (Download and Installation)
        
        Notes
        -----
        By default, we suppose that the input Hi-C data are corrected appropriately.
        Otherwise, systematic biases in source data will negatively impact chromatin
        interaction selection and then parameter calculation. Several correction schemes
        are available online:
        
        .. [1] Yaffe E, Tanay A. Probabilistic modeling of Hi-C contact maps eliminates
           systematic biases to characterize global chromosomal architecture. Nat Genet,
           2011, 43: 1059-65.
        
        .. [2] Imakaev M, Fudenberg G, McCord RP et al. Iterative correction of Hi-C data
           reveals hallmarks ofchromosome organization. Nat Methods, 2012, 9: 999-1003.
        
        .. [3] Hu M, Deng K, Selvaraj S et al. HiCNorm: removing biases in Hi-C data via
           Poisson regression. Bioinformatics, 2012, 28: 3131-3.
        
Keywords: chromosome structure feature Hi-C TAD CONISS polygon
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
Classifier: Topic :: Scientific/Engineering :: Mathematics
