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Article: Differential variability analysis of gene expression and its application to human diseases

TitleDifferential variability analysis of gene expression and its application to human diseases
Authors
Issue Date2008
Citation
Bioinformatics, 2008, v. 24, n. 13 How to Cite?
AbstractMotivation: Current microarray analyses focus on identifying sets of genes that are differentially expressed (DE) or differentially coexpressed (DC) in different biological states (e.g. diseased versus non-diseased). We observed that in many human diseases, some genes have a significantincrease or decrease in expression variability (variance). Asthese observed changes in expression variability may be caused by alteration of the underlying expression dynamics, such differential variability (DV) patterns are also biologically interesting. Results: Here we propose a novel analysis for changes in gene expression variability between groups of amples, which we call differential variability analysis. We introduce the concept of differential variability (DV), and present a simple procedure for identifying DV genes from microarray data. Our procedure is evaluated with simulated and real microarray datasets. The effect of data preprocessing methods on identification of DV gene is investigated. The biological significance of DV analysis is demonstrated with four human disease datasets. The relationships among DV, DE and DC genes are investigated. The results suggest that changes in expression variability are associated with changes in coexpression pattern, which imply that DV is not merely stochastic noise, but informative signal. © 2008 The Author(s).
Persistent Identifierhttp://hdl.handle.net/10722/262617
ISSN
2023 Impact Factor: 4.4
2023 SCImago Journal Rankings: 2.574
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorHo, Joshua W.K.-
dc.contributor.authorStefani, Maurizio-
dc.contributor.authorDos Remedios, Cristobal G.-
dc.contributor.authorCharleston, Michael A.-
dc.date.accessioned2018-10-08T02:46:33Z-
dc.date.available2018-10-08T02:46:33Z-
dc.date.issued2008-
dc.identifier.citationBioinformatics, 2008, v. 24, n. 13-
dc.identifier.issn1367-4803-
dc.identifier.urihttp://hdl.handle.net/10722/262617-
dc.description.abstractMotivation: Current microarray analyses focus on identifying sets of genes that are differentially expressed (DE) or differentially coexpressed (DC) in different biological states (e.g. diseased versus non-diseased). We observed that in many human diseases, some genes have a significantincrease or decrease in expression variability (variance). Asthese observed changes in expression variability may be caused by alteration of the underlying expression dynamics, such differential variability (DV) patterns are also biologically interesting. Results: Here we propose a novel analysis for changes in gene expression variability between groups of amples, which we call differential variability analysis. We introduce the concept of differential variability (DV), and present a simple procedure for identifying DV genes from microarray data. Our procedure is evaluated with simulated and real microarray datasets. The effect of data preprocessing methods on identification of DV gene is investigated. The biological significance of DV analysis is demonstrated with four human disease datasets. The relationships among DV, DE and DC genes are investigated. The results suggest that changes in expression variability are associated with changes in coexpression pattern, which imply that DV is not merely stochastic noise, but informative signal. © 2008 The Author(s).-
dc.languageeng-
dc.relation.ispartofBioinformatics-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.titleDifferential variability analysis of gene expression and its application to human diseases-
dc.typeArticle-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1093/bioinformatics/btn142-
dc.identifier.pmid18586739-
dc.identifier.scopuseid_2-s2.0-46249103142-
dc.identifier.volume24-
dc.identifier.issue13-
dc.identifier.spagenull-
dc.identifier.epagenull-
dc.identifier.eissn1460-2059-
dc.identifier.isiWOS:000257169700067-

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