Construction, Visualisation, and Clustering of Transcription Networks from Microarray Expression Data

Freeman, Tom C.; Goldovsky, Leon; Brosch, Markus; Van Dongen, Stijn; Mazière, Pierre; Grocock, Russell J.; Freilich, Shiri; Thornton, Janet; Enright, Anton J.
October 2007
PLoS Computational Biology;Oct2007, Vol. 3 Issue 10, pe206
Academic Journal
Network analysis transcends conventional pairwise approaches to data analysis as the context of components in a network graph can be taken into account. Such approaches are increasingly being applied to genomics data, where functional linkages are used to connect genes or proteins. However, while microarray gene expression datasets are now abundant and of high quality, few approaches have been developed for analysis of such data in a network context. We present a novel approach for 3-D visualisation and analysis of transcriptional networks generated from microarray data. These networks consist of nodes representing transcripts connected by virtue of their expression profile similarity across multiple conditions. Analysing genome-wide gene transcription across 61 mouse tissues, we describe the unusual topography of the large and highly structured networks produced, and demonstrate how they can be used to visualise, cluster, and mine large datasets. This approach is fast, intuitive, and versatile, and allows the identification of biological relationships that may be missed by conventional analysis techniques. This work has been implemented in a freely available open-source application named BioLayout Express3D.


Related Articles

  • Genetic Analysis of Variation in Gene Expression in Arabidopsis thaliana. Vuylsteke, Marnik; van Eeuwijk, Fred; van Hummelen, Paul; Kuiper, Martin; Zabeau, Marc // Genetics;Nov2005, Vol. 171 Issue 3, p1267 

    In Arabidopsis thaliana, significant efforts to determine the extent of genomic variation between phenotypically divergent accessions are under way, but virtually nothing is known about variation at the transcription level. We used microarrays to examine variation in transcript abundance an long...

  • Data quality in genomics and microarrays. Hanlee Ji; Davis, Ronald W. // Nature Biotechnology;Sep2006, Vol. 24 Issue 9, p1112 

    The article reports on the significance of objective quality control indices in facilitating clinical implementation of DNA microarrays for transcriptional profiling and in genomics. The development of the Microarray Quality Control and the External RNA Controls Consortium projects set the basis...

  • Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships. Junhee Seok; Kaushal, Amit; Davis, Ronald W.; Wenzhong Xiao // BMC Bioinformatics;2010 Supplement 1, Vol. 11, Special section p1 

    Background: The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the...

  • Genevestigator Transcriptome Meta-Analysis and Biomarker Search Using Rice and Barley Gene Expression Databases. Zimmermann, Philip; Laule, Oliver; Schmitz, Josy; Hruz, Tomas; Bleuler, Stefan; Gruissem, Wilhelm // Molecular Plant (Oxford University Press / USA);Sep2008, Vol. 1 Issue 5, p851 

    The wide-spread use of microarray technologies to study plant transcriptomes has led to important discoveries and to an accumulation of profiling data covering a wide range of different tissues, developmental stages, perturbations, and genotypes. Querying a large number of microarray experiments...

  • Validation of oligoarrays for quantitative exploration of the transcriptome. Nygaard, Vigdis; Fang Liu; Holden, Marit; Kuo, Winston P.; Trimarchi, Jeff; Ohno-Machado, Lucila; Cepko, Connie L.; Frigessi, Arnoldo; Glad, Ingrid K.; van de Wiel, Mark A.; Hovig, Eivind; Heidi Lyng // BMC Genomics;2008, Vol. 9, Special section p1 

    Background: Oligoarrays have become an accessible technique for exploring the transcriptome, but it is presently unclear how absolute transcript data from this technique compare to the data achieved with tag-based quantitative techniques, such as massively parallel signature sequencing (MPSS)...

  • Functional Genomics of 5- to 8-Cell Stage Human Embryos by Blastomere Single-Cell cDNA Analysis. Galán, Amparo; Montaner, David; Póo, M. Eugenia; Valbuena, Diana; Ruiz, Verónica; Aguilar, Cristóbal; Dopazo, Joaquín; Simón, Carlos // PLoS ONE;2010, Vol. 5 Issue 10, p1 

    Blastomere fate and embryonic genome activation (EGA) during human embryonic development are unsolved areas of high scientific and clinical interest. Forty-nine blastomeres from 5- to 8-cell human embryos have been investigated following an efficient single-cell cDNA amplification protocol to...

  • Minimum information about a microarray experiment (MIAME)?toward standards for microarray data. Brazma, Alvis; Hingamp, Pascal; Quackenbush, John; Sherlock, Gavin; Spellman, Paul; Stoeckert, Chris; Aach, John; Ansorge, Wilhelm; Ball, Catherine A.; Causton, Helen C.; Gaasterland, Terry; Glenisson, Patrick; Holstege, Frank C.P.; Kim, Irene F.; Markowitz, Victor; Matese, John C.; Parkinson, Helen; Robinson, Alan; Sarkans, Ugis // Nature Genetics;Dec2001, Vol. 29 Issue 4, p365 

    Microarray analysis has become a widely used tool for the generation of gene expression data on a genomic scale. Although many significant results have been derived from microarray studies, one limitation has been the lack of standards for presenting and exchanging such data. Here we present a...

  • Gene expression meets genome annotation. Gaasterland, Terry // Nature Genetics;Nov99 Supplement, Vol. 23, p19 

    Presents an abstract for the article on the integration of genome sequence annotation and cDNA microarray gene expression data.

  • Topoisomerase II inhibition involves characteristic chromosomal expression patterns. Reymann, Susanne; Borlak, Jürgen // BMC Genomics;2008, Vol. 9, Special section p1 

    Background: The phenomenon of co-localization of transcriptionally upregulated genes showing similar expression levels is known across all eukaryotic genomes. We recently mapped the Aroclor 1254-regulated transcriptome back onto the genome and provided evidence for the statistically significant...


Read the Article


Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics