Skip Navigation


Bioinformatics Advance Access originally published online on April 19, 2005
Bioinformatics 2005 21(13):2988-2993; doi:10.1093/bioinformatics/bti457
This Article
Right arrow Full Text Freely available
Right arrow FREE Full Text (Print PDF) Freely available
Right arrow All Versions of this Article:
21/13/2988    most recent
bti457v1
Right arrow Comments: Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when Comments are posted
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 arrow Search for citing articles in:
ISI Web of Science (45)
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Al-Shahrour, F.
Right arrow Articles by Dopazo, J.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Al-Shahrour, F.
Right arrow Articles by Dopazo, J.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oupjournals.org

Discovering molecular functions significantly related to phenotypes by combining gene expression data and biological information

Fátima Al-Shahrour , Ramón Díaz-Uriarte 1 and Joaquín Dopazo *

Department of Bioinformatics, and Functional Genomics Node (INB), Centro de Investigación Príncipe Felipe Autopista del Saler 16, 46013 Valencia, Spain
1Bioinformatics Unit, Centro Nacional de Investigaciones Oncológicas (CNIO) Melchor Fernández Almagro 3, 28029 Madrid, Spain

*To whom correspondence should be addressed.

Motivation: The analysis of genome-scale data from different high throughput techniques can be used to obtain lists of genes ordered according to their different behaviours under distinct experimental conditions corresponding to different phenotypes (e.g. differential gene expression between diseased samples and controls, different response to a drug, etc.). The order in which the genes appear in the list is a consequence of the biological roles that the genes play within the cell, which account, at molecular scale, for the macroscopic differences observed between the phenotypes studied. Typically, two steps are followed for understanding the biological processes that differentiate phenotypes at molecular level: first, genes with significant differential expression are selected on the basis of their experimental values and subsequently, the functional properties of these genes are analysed. Instead, we present a simple procedure which combines experimental measurements with available biological information in a way that genes are simultaneously tested in groups related by common functional properties. The method proposed constitutes a very sensitive tool for selecting genes with significant differential behaviour in the experimental conditions tested.

Results: We propose the use of a method to scan ordered lists of genes. The method allows the understanding of the biological processes operating at molecular level behind the macroscopic experiment from which the list was generated. This procedure can be useful in situations where it is not possible to obtain statistically significant differences based on the experimental measurements (e.g. low prevalence diseases, etc.). Two examples demonstrate its application in two microarray experiments and the type of information that can be extracted.

Availability: The software used for the association of significant Gene Ontology (GO) terms to sets of genes is available at http://www.fatigo.org and http://www.babelomics.org. Software for ranking genes according to phenotypes is available in GEPAS (http://www.gepas.org). The multtest program from the bioconductor package is available at http://www.bioconductor.org/repository/devel/package/html/multtest.html.

Contact: jdopazo{at}ochoa.fib.es


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
 DevelopmentHome page
L. Zhang, M. Hammell, B. A. Kudlow, V. Ambros, and M. Han
Systematic analysis of dynamic miRNA-target interactions during C. elegans development
Development, September 15, 2009; 136(18): 3043 - 3055.
[Abstract] [Full Text] [PDF]

Home page
 Nucleic Acids ResHome page
I. Medina, D. Montaner, N. Bonifaci, M. A. Pujana, J. Carbonell, J. Tarraga, F. Al-Shahrour, and J. Dopazo
Gene set-based analysis of polymorphisms: finding pathways or biological processes associated to traits in genome-wide association studies
Nucleic Acids Res., July 1, 2009; 37(suppl_2): W340 - W344.
[Abstract] [Full Text] [PDF]

Home page
 Nucleic Acids ResHome page
J. Tarraga, I. Medina, J. Carbonell, J. Huerta-Cepas, P. Minguez, E. Alloza, F. Al-Shahrour, S. Vegas-Azcarate, S. Goetz, P. Escobar, et al.
GEPAS, a web-based tool for microarray data analysis and interpretation
Nucleic Acids Res., July 1, 2008; 36(suppl_2): W308 - W314.
[Abstract] [Full Text] [PDF]

Home page
 Nucleic Acids ResHome page
F. Al-Shahrour, J. Carbonell, P. Minguez, S. Goetz, A. Conesa, J. Tarraga, I. Medina, E. Alloza, D. Montaner, and J. Dopazo
Babelomics: advanced functional profiling of transcriptomics, proteomics and genomics experiments
Nucleic Acids Res., July 1, 2008; 36(suppl_2): W341 - W346.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
P. Minguez, F. Al-Shahrour, D. Montaner, and J. Dopazo
Functional profiling of microarray experiments using text-mining derived bioentities
Bioinformatics, November 15, 2007; 23(22): 3098 - 3099.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
G. Gamberoni, E. Lamma, G. Lodo, J. Marchesini, N. Mascellani, S. Rossi, S. Storari, L. Tagliavini, and S. Volinia
Fun&Co: identification of key functional differences in transcriptomes
Bioinformatics, October 15, 2007; 23(20): 2725 - 2732.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
F. Tai and W. Pan
Incorporating prior knowledge of predictors into penalized classifiers with multiple penalty terms
Bioinformatics, July 15, 2007; 23(14): 1775 - 1782.
[Abstract] [Full Text] [PDF]

Home page
 Nucleic Acids ResHome page
F. Al-Shahrour, P. Minguez, J. Tarraga, I. Medina, E. Alloza, D. Montaner, and J. Dopazo
FatiGO +: a functional profiling tool for genomic data. Integration of functional annotation, regulatory motifs and interaction data with microarray experiments
Nucleic Acids Res., July 13, 2007; 35(suppl_2): W91 - W96.
[Abstract] [Full Text] [PDF]

Home page
 Nucleic Acids ResHome page
R. Diaz-Uriarte, A. Alibes, E. R. Morrissey, A. Canada, O. M. Rueda, and M. L. Neves
Asterias: integrated analysis of expression and aCGH data using an open-source, web-based, parallelized software suite
Nucleic Acids Res., July 13, 2007; 35(suppl_2): W75 - W80.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
S.-B. Kim, S. Yang, S.-K. Kim, S. C. Kim, H. G. Woo, D. J. Volsky, S.-Y. Kim, and I.-S. Chu
GAzer: gene set analyzer
Bioinformatics, July 1, 2007; 23(13): 1697 - 1699.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
D. Huang and T. W. S. Chow
Identifying the biologically relevant gene categories based on gene expression and biological data: an example on prostate cancer
Bioinformatics, June 15, 2007; 23(12): 1503 - 1510.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
D. M. Kemp, N. R. Nirmala, and J. D. Szustakowski
Extending the pathway analysis framework with a test for transcriptional variance implicates novel pathway modulation during myogenic differentiation
Bioinformatics, June 1, 2007; 23(11): 1356 - 1362.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
J. J. Goeman and P. Buhlmann
Analyzing gene expression data in terms of gene sets: methodological issues
Bioinformatics, April 15, 2007; 23(8): 980 - 987.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
D. Nam, S.-B. Kim, S.-K. Kim, S. Yang, S.-Y. Kim, and I.-S. Chu
ADGO: analysis of differentially expressed gene sets using composite GO annotation
Bioinformatics, September 15, 2006; 22(18): 2249 - 2253.
[Abstract] [Full Text] [PDF]

Home page
 Nucleic Acids ResHome page
F. Al-Shahrour, P. Minguez, J. Tarraga, D. Montaner, E. Alloza, J. M. Vaquerizas, L. Conde, C. Blaschke, J. Vera, and J. Dopazo
BABELOMICS: a systems biology perspective in the functional annotation of genome-scale experiments.
Nucleic Acids Res., July 1, 2006; 34(Web Server issue): W472 - W476.
[Abstract] [Full Text] [PDF]

Home page
 Nucleic Acids ResHome page
D. Montaner, J. Tarraga, J. Huerta-Cepas, J. Burguet, J. M. Vaquerizas, L. Conde, P. Minguez, J. Vera, S. Mukherjee, J. Valls, et al.
Next station in microarray data analysis: GEPAS.
Nucleic Acids Res., July 1, 2006; 34(Web Server issue): W486 - W491.
[Abstract] [Full Text] [PDF]

Home page
 Nucleic Acids ResHome page
M. Scheer, F. Klawonn, R. Munch, A. Grote, K. Hiller, C. Choi, I. Koch, M. Schobert, E. Hartig, U. Klages, et al.
JProGO: a novel tool for the functional interpretation of prokaryotic microarray data using Gene Ontology information.
Nucleic Acids Res., July 1, 2006; 34(Web Server issue): W510 - W515.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
D. Huang and W. Pan
Incorporating biological knowledge into distance-based clustering analysis of microarray gene expression data
Bioinformatics, May 15, 2006; 22(10): 1259 - 1268.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
W. Pan
Incorporating gene functions as priors in model-based clustering of microarray gene expression data
Bioinformatics, April 1, 2006; 22(7): 795 - 801.
[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.