Published online 28 October 2004
Nucleic Acids Research, Vol. 32 No. 19 © Oxford University Press 2004; all rights reserved
Hypervariable genes—experimental error or hidden dynamics
Department of Arthritis and Immunology, Oklahoma Medical Research Foundation, Oklahoma City, OK 73104, USA and 1 Department of Pediatrics, University of Oklahoma College of Medicine, Oklahoma City, OK 73104, USA
* To whom correspondence should be addressed at Department of Arthritis and Immunology, Oklahoma Medical Research Foundation, 825 NE, 13th Street, Oklahoma City, OK 73104, USA. Tel: +1 405 271 7052; Fax: +1 405 271 1339; E-mail: igor-dozmorov{at}omrf.ouhsc.edu
Received June 1, 2004; Revised July 27, 2004; Accepted October 7, 2004
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.
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