Local-pooled-error test for identifying differentially expressed genes with a small number of replicated microarrays

Nitin Jain, Jayant Thatte, Thomas Braciale, Klaus Ley, Michael O'Connell, Jae K. Lee

Research output: Contribution to journalArticlepeer-review

92 Scopus citations


Motivation: In microarray studies gene discovery based on fold-change values is often misleading because error variability for each gene is heterogeneous under different biological conditions and intensity ranges. Several statistical testing methods for differential gene expression have been suggested, but some of these approaches are underpowered and result in high false positive rates because within-gene variance estimates are based on a small number of replicated arrays. Results: We propose to use local-pooled-error (LPE) estimates and robust statistical tests for evaluating significance of each gene's differential expression. Our LPE estimation is based on pooling errors within genes and between replicate arrays for genes in which expression values are similar. We have applied our LPE method to compare gene expression in naïve and activated CD8+ T-cells. Our results show that the LPE method effectively identifies significant differential-expression patterns with a small number of replicated arrays.

Original languageEnglish (US)
Pages (from-to)1945-1951
Number of pages7
Issue number15
StatePublished - Oct 12 2003
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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