Cargando…
Visualization of genomic data with the Hilbert curve
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 co...
Autor principal: | |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2009
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2677744/ https://www.ncbi.nlm.nih.gov/pubmed/19297348 http://dx.doi.org/10.1093/bioinformatics/btp152 |
_version_ | 1782166796243042304 |
---|---|
author | Anders, Simon |
author_facet | Anders, Simon |
author_sort | Anders, Simon |
collection | PubMed |
description | 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@fs.tum.de Supplementary information: Supplementary Data are available at Bioinformatics online. |
format | Text |
id | pubmed-2677744 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-26777442009-05-08 Visualization of genomic data with the Hilbert curve Anders, Simon Bioinformatics Original Papers 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@fs.tum.de Supplementary information: Supplementary Data are available at Bioinformatics online. Oxford University Press 2009-05-15 2009-03-17 /pmc/articles/PMC2677744/ /pubmed/19297348 http://dx.doi.org/10.1093/bioinformatics/btp152 Text en © 2009 The Author(s) http://creativecommons.org/licenses/by-nc/2.0/uk/ 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. |
spellingShingle | Original Papers Anders, Simon Visualization of genomic data with the Hilbert curve |
title | Visualization of genomic data with the Hilbert curve |
title_full | Visualization of genomic data with the Hilbert curve |
title_fullStr | Visualization of genomic data with the Hilbert curve |
title_full_unstemmed | Visualization of genomic data with the Hilbert curve |
title_short | Visualization of genomic data with the Hilbert curve |
title_sort | visualization of genomic data with the hilbert curve |
topic | Original Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2677744/ https://www.ncbi.nlm.nih.gov/pubmed/19297348 http://dx.doi.org/10.1093/bioinformatics/btp152 |
work_keys_str_mv | AT anderssimon visualizationofgenomicdatawiththehilbertcurve |