Hypervariable genes--experimental error or hidden dynamics.

Igor Dozmorov, Nicholas Knowlton, Yuhong Tang, Alan Shields, Parima Pathipvanich, James N. Jarvis, Michael Centola

Research output: Contribution to journalArticlepeer-review

32 Scopus citations

Abstract

In a homogeneous group of samples, not all genes of high variability stem from experimental errors in microarray experiments. These expression variations can be attributed to many factors including natural biological oscillations or metabolic processes. The behavior of these genes can tease out important clues about naturally occurring dynamic processes in the organism or experimental system under study. We developed a statistical procedure for the selection of genes with high variability denoted hypervariable (HV) genes. After the exclusion of low expressed genes and a stabilizing log-transformation, the majority of genes have comparable residual variability. Based on an F-test, HV genes are selected as having a statistically significant difference from the majority of variability stabilized genes measured by the 'reference group'. A novel F-test clustering technique, further noted as 'F-means clustering', groups HV genes with similar variability patterns, presumably from their participation in a common dynamic biological process. F-means clustering establishes, for the first time, groups of co-expressed HV genes and is illustrated with microarray data from patients with juvenile rheumatoid arthritis and healthy controls.

Original languageEnglish (US)
Pages (from-to)e147
JournalNucleic acids research
Volume32
Issue number19
DOIs
StatePublished - 2004

ASJC Scopus subject areas

  • Genetics

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