Skip to main content
Article thumbnail
Location of Repository

Exploratory Visual Analysis of Statistical Results from Microarray Experiments Comparing High and Low Grade Glioma

By David M. Reif, Mark A. Israel and Jason H. Moore


The biological interpretation of gene expression microarray results is a daunting challenge. For complex diseases such as cancer, wherein the body of published research is extensive, the incorporation of expert knowledge provides a useful analytical framework. We have previously developed the Exploratory Visual Analysis (EVA) software for exploring data analysis results in the context of annotation information about each gene, as well as biologically relevant groups of genes. We present EVA as a flexible combination of statistics and biological annotation that provides a straightforward visual interface for the interpretation of microarray analyses of gene expression in the most commonly occuring class of brain tumors, glioma. We demonstrate the utility of EVA for the biological interpretation of statistical results by analyzing publicly available gene expression profiles of two important glial tumors. The results of a statistical comparison between 21 malignant, high-grade glioblastoma multiforme (GBM) tumors and 19 indolent, low-grade pilocytic astrocytomas were analyzed using EVA. By using EVA to examine the results of a relatively simple statistical analysis, we were able to identify tumor class-specific gene expression patterns having both statistical and biological significance. Our interactive analysis highlighted the potential importance of genes involved in cell cycle progression, proliferation, signaling, adhesion, migration, motility, and structure, as well as candidate gene loci on a region of Chromosome 7 that has been implicated in glioma. Because EVA does not require statistical or computational expertise and has the flexibility to accommodate any type of statistical analysis, we anticipate EVA will prove a useful addition to the repertoire of computational methods used for microarray data analysis. EVA is available at no charge to academic users and can be found at

Topics: Systems Biology Special Issue
Publisher: Libertas Academica
OAI identifier:
Provided by: PubMed Central
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://www.pubmedcentral.nih.g... (external link)
  • (external link)
  • Suggested articles


    1. (2002). Accuracy and calibration of commercial oligonucleotide and custom cDNA microarrays.”
    2. (1999). Cancer surveillance series [corrected]: brain and other central nervous system cancers: recent trends in incidence and mortality”,
    3. (2003). CDD: a curated Entrez database of conserved domain alignments.”
    4. (2001). Distinctive molecular profi les of high-grade and low-grade gliomas based on oligonucleotide microarray analysis”,
    5. (2005). Entrez Gene: gene-centered information at
    6. (2005). Exploratory visual analysis of pharmacogenomic results.”
    7. (2001). Glioma cell invasion: regulation of metalloproteinase activity by TGF-beta.”
    8. (2003). HIPK2 regulates transforming growth factor-beta-induced c-Jun NH(2)-terminal kinase activation and apoptosis in human hepatoma cells”,
    9. (2001). Molecular cytogenetic analysis of glial tumors using spectral karyotyping and comparative genomic hybridization.”
    10. (2004). Online Mendelian Inheritance in Man.
    11. (2005). Ontological analysis of gene expression data: current tools, limitations, and open problems.”
    12. (2002). PAI-1 and EGFR expression in adult glioma tumors: toward a molecular prognostic classifi cation.”
    13. (2005). Proteomic studies on low- and high-grade human brain astrocytomas.”
    14. (2001). RefSeq and LocusLink: NCBI genecentered resources.”
    15. (2005). Signifi cance analysis of functional categories in gene expression studies: a structured permutation approach.”
    16. (2004). The Gene Ontology (GO) database and informatics resource.”
    17. (2004). The KEGG resource for deciphering the genome.”
    18. (2002). The WHO classifi cation of tumors of the nervous system.”
    19. (2001). Tubulin stimulates adenylyl cyclase activity in C6 glioma cells by bypassing the beta-adrenergic receptor: a potential mechanism of G protein activation”,
    20. (2006). Visual analysis of statistical results from microarray studies of human breast cancer.” Oncol.
    21. (2004). Zyxin interacts with the SH3 domains of the cytoskeletal proteins LIM-nebulette and Lasp-1.”

    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.