Related Experiment Video
Updated: Aug 17, 2026

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies
Published on: May 6, 2022
Pathways to the analysis of microarray data
R Keira Curtis1, Matej Oresic, Antonio Vidal-Puig
1University of Cambridge Department of Clinical Biochemistry, Box 232, Addenbrooke's Hospital, Hills Road, Cambridge, UK, CB2 2QR. rkc24@cam.ac.uk
Abstract:
The development of microarray technology allows the simultaneous measurement of the expression of many thousands of genes. The information gained offers an unprecedented opportunity to fully characterize biological processes. However, this challenge will only be successful if new tools for the efficient integration and interpretation of large datasets are available. One of these tools, pathway analysis, involves looking for consistent but subtle changes in gene expression by incorporating either pathway or functional annotations. We review several methods of pathway analysis and compare the performance of three, the binomial distribution, z scores, and gene set enrichment analysis, on two microarray datasets. Pathway analysis is a promising tool to identify the mechanisms that underlie diseases, adaptive physiological compensatory responses and new avenues for investigation.

