May 11, 2011

Nonlinear gene cluster analysis with labeling for microarray gene expression data in organ development

BMC Proceedings
Martin EhlerRobert F Bonner


The gene networks underlying closure of the optic fissure during vertebrate eye development are not well-understood. We use a novel clustering method based on nonlinear dimension reduction with data labeling to analyze microarray data from laser capture microdissected (LCM) cells at the site and developmental stages (days 10.5 to 12.5) of optic fissure closure. Our nonlinear methods created clusters of genes that mapped onto more specific biological processes and functions related to eye development as defined by Gene Ontology at lower false discovery rates than conventional linear cluster algorithms. Our new methods build on the advantages of LCM to isolate pure phenotypic populations within complex tissues in order to identify systems biology relationships among critical gene products expressed at lower copy number. The combination of LCM of embryonic organs, gene expression microarrays, and nonlinear dimension reduction with labeling is a potentially useful approach to extract subtle spatial and temporal co-variations within the gene regulatory networks that specify mammalian organogenesis and organ function. Our results motivate further analysis of nonlinear dimension reduction with labeling within other microarray data set...Continue Reading

  • References16
  • Citations6


  • References16
  • Citations6

Mentioned in this Paper

Eye Morphogenesis
Entire Retina
CDH4 gene
Transcription, Genetic
Candidate Disease Gene
Retinal Diseases

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