Intertwining threshold settings, biological data and database knowledge to optimize the selection of differentially expressed genes from microarray.

Paul Chuchana 1, 2, * Philippe Holzmuller 2 Frederic Vezilier 2 David Berthier 2 Isabelle Chantal 2 Dany Severac 3, 4 Jean Loup Lemesre 2 Gerard Cuny 2 Philippe Nirdé 5 Bruno Bucheton 2
* Auteur correspondant
1 Cellules souches mésenchymateuses, environnement articulaire et immunothérapies de la polyarthrite rhumatoide
2 INTERTRYP - Interactions hôtes-vecteurs-parasites dans les infections par des trypanosomatidae
3 IGF - Institut de Génomique Fonctionnelle
4 IGF MGX - Institut de Génomique Fonctionnelle - Montpellier GenomiX
5 IRCM - U896 Inserm - UM1 - Institut de recherche en cancérologie de Montpellier
Abstract : BACKGROUND: Many tools used to analyze microarrays in different conditions have been described. However, the integration of deregulated genes within coherent metabolic pathways is lacking. Currently no objective selection criterion based on biological functions exists to determine a threshold demonstrating that a gene is indeed differentially expressed. METHODOLOGY/PRINCIPAL FINDINGS: To improve transcriptomic analysis of microarrays, we propose a new statistical approach that takes into account biological parameters. We present an iterative method to optimise the selection of differentially expressed genes in two experimental conditions. The stringency level of gene selection was associated simultaneously with the p-value of expression variation and the occurrence rate parameter associated with the percentage of donors whose transcriptomic profile is similar. Our method intertwines stringency level settings, biological data and a knowledge database to highlight molecular interactions using networks and pathways. Analysis performed during iterations helped us to select the optimal threshold required for the most pertinent selection of differentially expressed genes. CONCLUSIONS/SIGNIFICANCE: We have applied this approach to the well documented mechanism of human macrophage response to lipopolysaccharide stimulation. We thus verified that our method was able to determine with the highest degree of accuracy the best threshold for selecting genes that are truly differentially expressed.
Type de document :
Article dans une revue
PLoS ONE, Public Library of Science, 2010, 5 (10), pp.e13518. 〈10.1371/journal.pone.0013518〉
Liste complète des métadonnées

Littérature citée [48 références]  Voir  Masquer  Télécharger
http://www.hal.inserm.fr/inserm-00532804
Contributeur : Paul Chuchana <>
Soumis le : vendredi 5 novembre 2010 - 12:24:57
Dernière modification le : mercredi 10 octobre 2018 - 14:28:10
Document(s) archivé(s) le : dimanche 6 février 2011 - 02:32:33

Fichier

journal.pone.0013518.pdf
Fichiers éditeurs autorisés sur une archive ouverte

Identifiants

Collections

CIRAD | FNCLCC | VALDAURELLE | AGROPOLIS | BS | UNIV-MONTPELLIER | IRD | UNIV-LYON1

Citation

Paul Chuchana, Philippe Holzmuller, Frederic Vezilier, David Berthier, Isabelle Chantal, et al.. Intertwining threshold settings, biological data and database knowledge to optimize the selection of differentially expressed genes from microarray.. PLoS ONE, Public Library of Science, 2010, 5 (10), pp.e13518. 〈10.1371/journal.pone.0013518〉. 〈inserm-00532804〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

466

Téléchargements de fichiers

251

Contact

support.ccsd.cnrs.fr
hal.support@ccsd.cnrs.fr
Logo CCSD