Methodology article
Graph-based iterative Group Analysis enhances microarray interpretation
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* Corresponding author: Rainer Breitling r.breitling@bio.gla.ac.uk
1 Plant Science Group, Institute of Biomedical and Life Sciences, University of Glasgow, Glasgow G12 8QQ, United Kingdom
2 Bioinformatics Research Centre, Department of Computing Science, University of Glasgow, Glasgow G12 8QQ, United Kingdom
3 Sir Henry Wellcome Functional Genomics Facility, Institute of Biomedical and Life Sciences, University of Glasgow, Glasgow G12 8QQ, United Kingdom
BMC Bioinformatics 2004, 5:100 doi:10.1186/1471-2105-5-100
Published: 23 July 2004Additional files
Additional File 1:
GiGA program. For use from the Windows command line.
Format: EXE Size: 671KB Download file
Additional File 3:
GiGA manual. Describes the use of GiGA applied to the example data (Additional files 4 to 6).
Format: PDF Size: 104KB Download file
This file can be viewed with: Adobe Acrobat Reader
Additional File 4:
Gene expression data. Sorted list of genes, based on expression during the yeast diauxic shift.
Format: TXT Size: 339KB Download file
Additional File 5:
Evidence network. List of gene pairs connecting genes whenever their gene products are enzymes that share a common substrate. Based on annotation derived from SwissProt.
Format: TXT Size: 957KB Download file
Additional File 6:
Genenames file. Contains descriptive names of the yeast genes contained in Additional file 4.
Format: TXT Size: 294KB Download file
Additional File 7:
Example output in text format. List of significantly affected subgraphs detected in the experimental data (Additional file 4) using GiGA with default settings.
Format: TXT Size: 5KB Download file
Additional File 8:
Example output in graph-description language format. Contains the same results as Additional file 7, but in a format that can be visualized and explored using graph-layout software, e.g. aiSee, which is freely available for academics at http://www.aisee.com webcite.
Format: GDL Size: 24KB Download file