Skip Navigation


Bioinformatics Advance Access originally published online on January 19, 2008
Bioinformatics 2008 24(5):682-688; doi:10.1093/bioinformatics/btn017
This Article
Right arrow Full Text
Right arrow Full Text (Print PDF)
Right arrow Supplementary Data
Right arrow All Versions of this Article:
24/5/682    most recent
btn017v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Bréhélin, L.
Right arrow Articles by Martin, O.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Bréhélin, L.
Right arrow Articles by Martin, O.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author 2008. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Using repeated measurements to validate hierarchical gene clusters

Laurent Bréhélin 1,*,{dagger}, Olivier Gascuel 1 and Olivier Martin 2,3,{dagger}

1Méthodes et Algorithmes pour la Bioinformatique, LIRMM, CNRS - University Montpellier II, 2INRA, Unité protéomique, 2 Place Viala, 34060 Montpellier Cédex 1 and 3INRA, Unité Biostatistique et Processus Spatiaux, 84914 Avignon Cédex 9, France

*To whom correspondence should be addressed.


  Abstract

Motivation: Hierarchical clustering is a common approach to study protein and gene expression data. This unsupervised technique is used to find clusters of genes or proteins which are expressed in a coordinated manner across a set of conditions. Because of both the biological and technical variability, experimental repetitions are generally performed. In this work, we propose an approach to evaluate the stability of clusters derived from hierarchical clustering by taking repeated measurements into account.

Results: The method is based on the bootstrap technique that is used to obtain pseudo-hierarchies of genes from resampled datasets. Based on a fast dynamic programming algorithm, we compare the original hierarchy to the pseudo-hierarchies and assess the stability of the original gene clusters. Then a shuffling procedure can be used to assess the significance of the cluster stabilities. Our approach is illustrated on simulated data and on two microarray datasets. Compared to the standard hierarchical clustering methodology, it allows to point out the dubious and stable clusters, and thus avoids misleading interpretations.

Availability: The programs were developed in C and R languages.

Contact: brehelin{at}lirmm.fr

Supplementary information: Supplementary Material and source code are available at address http://www.lirmm.fr/~brehelin/Stability/

Associate Editor: Trey Ideker

{dagger}Both authors contributed equally to this work.

Received on October 2, 2007; revised on December 11, 2007; accepted on January 9, 2008

Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 BrainHome page
J. Fassunke, M. Majores, A. Tresch, P. Niehusmann, A. Grote, S. Schoch, and A. J. Becker
Array analysis of epilepsy-associated gangliogliomas reveals expression patterns related to aberrant development of neuronal precursors
Brain, September 26, 2008; (2008) awn233v1.
[Abstract] [Full Text] [PDF]


Disclaimer:
Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.