Year: 2009
Type: article
Abstract: UNLABELLED: 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/.
Source: Bioinformatics
Author: Simon Anders
Institution: European Bioinformatics Institute
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,989
Funder: European Commission
OpenAlex ID: W2102771000