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Bioinformatics. 2016 Aug 1;32(15):2372-4. doi: 10.1093/bioinformatics/btw161. Epub 2016 Mar 24.

HilbertCurve: an R/Bioconductor package for high-resolution visualization of genomic data.

Author information

  • 1Division of Theoretical Bioinformatics Heidelberg Center for Personalized Oncology (DKFZ-HIPO), German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • 2Division of Theoretical Bioinformatics Heidelberg Center for Personalized Oncology (DKFZ-HIPO), German Cancer Research Center (DKFZ), Heidelberg, Germany Department for Bioinformatics and Functional Genomics, Institute for Pharmacy and Molecular Biotechnology (IPMB) and BioQuant, Heidelberg University, Heidelberg, Germany.
  • 3Division of Theoretical Bioinformatics.

Abstract

: Hilbert curves enable high-resolution visualization of genomic data on a chromosome- or genome-wide scale. Here we present the HilbertCurve package that provides an easy-to-use interface for mapping genomic data to Hilbert curves. The package transforms the curve as a virtual axis, thereby hiding the details of the curve construction from the user. HilbertCurve supports multiple-layer overlay that makes it a powerful tool to correlate the spatial distribution of multiple feature types.

AVAILABILITY AND IMPLEMENTATION:

The HilbertCurve package and documentation are freely available from the Bioconductor project: http://www.bioconductor.org/packages/devel/bioc/html/HilbertCurve.html

CONTACT:

m.schlesner@dkfz.de

SUPPLEMENTARY INFORMATION:

Supplementary data are available at Bioinformatics online.

PMID:
27153599
DOI:
10.1093/bioinformatics/btw161
[PubMed - in process]
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