{ "info": { "author": "XiaoTao Wang", "author_email": "wangxiaotao868@163.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 3 - Alpha", "Intended Audience :: Science/Research", "License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)", "Operating System :: POSIX", "Programming Language :: Python :: 2.6", "Programming Language :: Python :: 2.7", "Topic :: Scientific/Engineering :: Bio-Informatics" ], "description": "Introduction\n============\n3C-based techniques(5C, Hi-C) have revealed the existence of topologically\nassociating domains(TADs), a pervasive sub-megabase scale structure of chromosome.\nTADs are contiguous regions in which loci interact much more frequently with\neach other than with loci out of the region. Visually, TADs appear as square\nblocks along the diagonal on a heatmap.\n\nThere are various methods for TAD identification [1]_, [2]_. Most methods\napply a two-step scheme: First, transform TAD or boundary signal into 1d\nprofile using some statistic(e.g. Directionality Index, DI); Then, use the\n1d profile to identify potential boundaries and produce a set of discrete\nnon-overlapping TADs. However, the organization of chromosome structure is\nalways intricate and hierarchical. Phillips-Cremins JE et al. [3]_ utilized\na modified DI of multiple scales subdivided TADs into smaller subtopologies (sub-TADs)\nusing 5C data. Here, I extend their algorithm to the whole genome and develop\nthis software.\n\n*calTADs* are tested on traditional [4]_ and *in-situ* [5]_ Hi-C data, both generating\nreasonable results.\n\nInstallation\n============\nPlease check the file \"INSTALL.rst\" in the distribution.\n\nLinks\n=====\n- `Repository `_\n- `PyPI `_\n\nUsage\n=====\nOpen a terminal, type ``calTADs -h`` for help information.\n\ncalTADs contains a process management system, so you can submit the same\ncommand repeatedly to utilize the parallel power as much as possible.\n\nReference\n=========\n.. [1] Dixon JR, Selvaraj S, Yue F et al. Topological domains in\n mammalian genomes identified by analysis of chromatin interactions.\n Nature, 2012, 485: 376-380.\n\n.. [2] Sexton T, Yaffe E, Kenigsberg E et al. Three-dimensional folding\n and functional organization principles of the Drosophila genome.\n Cell, 2012, 148: 458-472.\n\n.. [3] Phillips-Cremins JE, Sauria ME, Sanyal A et al. Architectural protein\n subclasses shape 3D organization of genomes during lineage commitment.\n Cell, 2013, 153(6):1281-95.\n\n.. [4] Lieberman-Aiden E, van Berkum NL, Williams L et al. Comprehensive\n mapping of long-range interactions reveals folding principles of the\n human genome. Science, 2009, 326: 289-293.\n\n.. [5] Rao SS, Huntley MH, Durand NC. 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