A Global Test for Groups of Genes: Testing Association With a Clinical Outcome

Bioinformatics. 2004 Jan 1;20(1):93-9. doi: 10.1093/bioinformatics/btg382.


Motivation: This paper presents a global test to be used for the analysis of microarray data. Using this test it can be determined whether the global expression pattern of a group of genes is significantly related to some clinical outcome of interest. Groups of genes may be any size from a single gene to all genes on the chip (e.g. known pathways, specific areas of the genome or clusters from a cluster analysis).

Result: The test allows groups of genes of different size to be compared, because the test gives one p-value for the group, not a p-value for each gene. Researchers can use the test to investigate hypotheses based on theory or past research or to mine gene ontology databases for interesting pathways. Multiple testing problems do not occur unless many groups are tested. Special attention is given to visualizations of the test result, focussing on the associations between samples and showing the impact of individual genes on the test result.

Availability: An R-package globaltest is available from http://www.bioconductor.org

Publication types

  • Comparative Study
  • Evaluation Study
  • Validation Study

MeSH terms

  • Algorithms
  • Cluster Analysis
  • Diagnosis, Computer-Assisted / methods*
  • Feasibility Studies
  • Gene Expression Profiling / methods*
  • Genetic Predisposition to Disease / genetics*
  • Genetic Testing / methods*
  • Humans
  • Leukemia / diagnosis
  • Leukemia / genetics
  • Models, Genetic*
  • Models, Statistical*
  • Oligonucleotide Array Sequence Analysis / methods*
  • Reproducibility of Results
  • Sample Size
  • Sensitivity and Specificity
  • Statistics as Topic*