The Arabidopsis co-expression tool (ACT): A WWW-based tool and database for microarray-based gene expression analysis

Chih-Hung Jen, Iain W. Manfield, Ioannis Michalopoulos, John W. Pinney, William G. T. Willats, Philip M. Gilmartin, David R. Westhead

Research output: Contribution to journalArticlepeer-review

65 Citations (Scopus)

Abstract

We present a new WWW-based tool for plant gene analysis, the Arabidopsis Co-Expression Tool (ACT), based on a large Arabidopsis thaliana microarray data set obtained from the Nottingham Arabidopsis Stock Centre. The co-expression analysis tool allows users to identify genes whose expression patterns are correlated across selected experiments or the complete data set. Results are accompanied by estimates of the statistical significance of the correlation relationships, expressed as probability (P) and expectation (E) values. Additionally, highly ranked genes on a correlation list can be examined using the novel CLIQUE FINDER tool to determine the sets of genes most likely to be regulated in a similar manner. In combination, these tools offer three levels of analysis: creation of correlation lists of co-expressed genes, refinement of these lists using two-dimensional scatter plots, and dissection into cliques of co-regulated genes. We illustrate the applications of the software by analysing genes encoding functionally related proteins, as well as pathways involved in plant responses to environmental stimuli. These analyses demonstrate novel biological relationships underlying the observed gene co-expression patterns. To demonstrate the ability of the software to develop testable hypotheses on gene function within a defined biological process we have used the example of cell wall biosynthesis genes. The resource is freely available at http://www.arabidopsis.leeds.ac.uk/ACT/.
Original languageEnglish
Pages (from-to)336-348
Number of pages13
JournalThe Plant Journal
Volume46
Issue number2
DOIs
Publication statusPublished - 1 Apr 2006

Keywords

  • bioinformatics
  • co-expression
  • plants
  • gene networks
  • regulation

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