The cyclohedron test for finding periodic genes in time course expression studies

Jason Ryder Morton, Lior Pachter, Anne Shiu, Bernd Sturmfels

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

The problem of finding periodically expressed genes from time course microarray experiments is at the center of numerous efforts to identify the molecular components of biological clocks. We present a new approach to this problem based on the cyclohedron test, which is a rank test inspired by recent advances in algebraic combinatorics. The test has the advantage of being robust to measurement errors, and can be used to ascertain the significance of top-ranked genes. We apply the test to recently published measurements of gene expression during mouse somitogenesis and find 32 genes that collectively are significant. Among these are previously identified periodic genes involved in the Notch/FGF and Wnt signaling pathways, as well as novel candidate genes that may play a role in regulating the segmentation clock. These results confirm that there are an abundance of exceptionally periodic genes expressed during somitogenesis. The emphasis of this paper is on the statistics and combinatorics that underlie the cyclohedron test and its implementation within a multiple testing framework.

Original languageEnglish (US)
Article number21
JournalStatistical Applications in Genetics and Molecular Biology
Volume6
Issue number1
DOIs
StatePublished - Aug 15 2007

Fingerprint

Genes
Gene
Combinatorics
Clocks
Biological Clocks
Rank Test
Wnt Signaling Pathway
Multiple Testing
Signaling Pathways
Notch
Microarrays
Measurement errors
Gene expression
Measurement Error
Microarray
Gene Expression
Mouse
Segmentation
Statistics
Testing

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Molecular Biology
  • Genetics
  • Computational Mathematics

Cite this

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The cyclohedron test for finding periodic genes in time course expression studies. / Morton, Jason Ryder; Pachter, Lior; Shiu, Anne; Sturmfels, Bernd.

In: Statistical Applications in Genetics and Molecular Biology, Vol. 6, No. 1, 21, 15.08.2007.

Research output: Contribution to journalArticle

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