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DOI: 10.4230/LIPIcs.WABI.2017.22
URN: urn:nbn:de:0030-drops-76446
URL: http://drops.dagstuhl.de/opus/volltexte/2017/7644/
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Roayaei Ardakany, Abbas ; Lonardi, Stefano

Efficient and Accurate Detection of Topologically Associating Domains from Contact Maps

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Abstract

Continuous improvements to high-throughput conformation capture (Hi-C) are revealing richerinformation about the spatial organization of the chromatin and its role in cellular functions.Several studies have confirmed the existence of structural features of the genome 3D organiza-tion that are stable across cell types and conserved across species, calledtopological associatingdomains(TADs). The detection of TADs has become a critical step in the analysis of Hi-C data,e.g., to identify enhancer-promoter associations. Here we presentEast, a novel TAD identifi-cation algorithm based on fast 2D convolution of Haar-like features, that is as accurate as thestate-of-the-art method based on the directionality index, but 75-80x faster.Eastis availablein the public domain at https://github.com/ucrbioinfo/EAST.

BibTeX - Entry

@InProceedings{roayaeiardakany_et_al:LIPIcs:2017:7644,
  author =	{Abbas Roayaei Ardakany and Stefano Lonardi},
  title =	{{Efficient and Accurate Detection of Topologically Associating Domains from Contact Maps}},
  booktitle =	{17th International Workshop on Algorithms in Bioinformatics (WABI 2017)},
  pages =	{22:1--22:11},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-050-7},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{88},
  editor =	{Russell Schwartz and Knut Reinert},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2017/7644},
  URN =		{urn:nbn:de:0030-drops-76446},
  doi =		{10.4230/LIPIcs.WABI.2017.22},
  annote =	{Keywords: Chromatin, TADs, 3D genome, Hi-C, contact maps}
}

Keywords: Chromatin, TADs, 3D genome, Hi-C, contact maps
Seminar: 17th International Workshop on Algorithms in Bioinformatics (WABI 2017)
Issue Date: 2017
Date of publication: 03.08.2017


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