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Bioinformatics Advance Access published online on March 28, 2007
Bioinformatics, doi:10.1093/bioinformatics/btm116
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© The Author (2007). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Extending the pathway analysis framework with a test for transcriptional variance implicates novel pathway modulation during myogenic differentiation.

Daniel Kemp 1, N. R. Nirmala 2 and Joseph D. Szustakowski 2,*

Novartis Institutes for BioMedical Research, 1Diabetes and Metabolism Disease Area and 2Genome and Proteome Sciences 250 Massachusetts Avenue, Cambridge, MA, 02139

*To whom correspondence should be addressed. Joseph D. Szustakowski, E-mail: joseph.szustakowski{at}novartis.com


  Abstract

Motivation: We describe an extension of the pathway-based enrichment approach to analyzing microarray data via a robust test for transcriptional variance. The use of a variance test is intended to identify additional patterns of transcriptional regulation in which many genes in a pathway are up- and down-regulated. Such patterns may be indicative of the reciprocal regulation of pathway activators and inhibitors or of the differential regulation of separate biological sub-processes and should extend the number of detectable patterns of transcriptional modulations.

Results: We validated this new statistical approach on a microarray experiment that captures the temporal transcriptional profile of muscle differentiation in mouse C2C12 cells. Comparisons of the transcriptional state of myoblasts and differentiated myotubes via a robust variance test implicated several novel pathways in muscle cell differentiation previously overlooked by a standard enrichment analysis. Specifically, pathways involved in cell structure, calcium mediated signaling, and muscle specific signaling were identified as differentially modulated based on their increased transcriptional variance. These biologically relevant results validate this approach and demonstrate the flexible nature of pathway based methods of data analysis.

Availability: The software is available as Supplemental Information.

Associate Editor: Prof. Martin Bishop

Received on October 30, 2006; revised on March 7, 2007; accepted on March 16, 2007

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