Analysis of dose-response effects on gene expression data with comparison of two microarray platforms

Jianhua Hu, Mini Kapoor, Wei Zhang, Stanley R. Hamilton, Kevin R. Coombes

Research output: Contribution to journalArticlepeer-review

21 Scopus citations

Abstract

Motivation: The problems of analyzing dose effects on gene expression are gaining attention in biomedical research. A specific challenge is to detect genes with expression levels that change according to dose levels in a non-random manner, but nonetheless may be considered as potential biomarkers. Method: We are among the first to formally apply a tool that uses an isotonic (monotonic) regression approach to this area of study. We introduce a test statistic to select genes with significant dose-response expression in a monotonic fashion based on a permutation procedure. We then compare the results with those achieved from the application of a likelihood ratio-based test. Results: We apply the isotonic regression approach to a study of gene expression in the RKO colon carcinoma cell line in response to varying dosage levels of the chemotherapeutic agent 5-fluorouracil. A feature of both Affymetrix and printed 75mer oligomer cDNA arrays produced from the same samples provides an opportunity to compare the two microarray platforms.

Original languageEnglish (US)
Pages (from-to)3524-3529
Number of pages6
JournalBioinformatics
Volume21
Issue number17
DOIs
StatePublished - Sep 1 2005
Externally publishedYes

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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