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Bioinformatics Advance Access originally published online on March 17, 2009
Bioinformatics 2009 25(10):1231-1235; doi:10.1093/bioinformatics/btp152
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© 2009 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Visualization of genomic data with the Hilbert curve

Simon Anders

European Bioinformatics Institute (EMBL-EBI), Hinxton, CB10 1SD, UK


  Abstract

In many genomic studies, one works with genome-position-dependent data, e.g. ChIP-chip or ChIP-Seq scores. Using conventional tools, it can be difficult to get a good feel for the data, especially the distribution of features. This article argues that the so-called Hilbert curve visualization can complement genome browsers and help to get further insights into the structure of one's data. This is demonstrated with examples from different use cases. An open-source application, called HilbertVis, is presented that allows the user to produce and interactively explore such plots.

Availability: http://www.ebi.ac.uk/huber-srv/hilbert/

Contact: sanders{at}fs.tum.de

Supplementary information: Supplementary Data are available at Bioinformatics online.

Associate Editor: John Quackenbush

Received on August 27, 2008; revised on March 11, 2009; accepted on March 14, 2009

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