May 2005
Volume 46, Issue 13
Free
ARVO Annual Meeting Abstract  |   May 2005
Tight Cluster Analysis of Microarray Data Reveals Distinctive Patterns of Co–Regulation in Lacrimal Gland Gene Expression
Author Affiliations & Notes
  • W.D. Mathers
    Ophthalmology Dept, Casey Eye Institute, Oregon Health & Science University, Portland, OR
  • D. Choi
    Biostatistics Div.–Public Health and Preventive Medicine, Oregon Health & Science University, Portland, OR
  • Y. Fang
    Ophthalmology Dept, Casey Eye Institute, Oregon Health & Science University, Portland, OR
  • Footnotes
    Commercial Relationships  W.D. Mathers, None; D. Choi, None; Y. Fang, None.
  • Footnotes
    Support  RPB Inc.
Investigative Ophthalmology & Visual Science May 2005, Vol.46, 4423. doi:
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      W.D. Mathers, D. Choi, Y. Fang; Tight Cluster Analysis of Microarray Data Reveals Distinctive Patterns of Co–Regulation in Lacrimal Gland Gene Expression . Invest. Ophthalmol. Vis. Sci. 2005;46(13):4423.

      Download citation file:


      © ARVO (1962-2015); The Authors (2016-present)

      ×
  • Supplements
Abstract

Abstract: : Purpose:To identify co–regulated genes with unique gene expression patterns in the mouse lacrimal gland following corneal injury by tight cluster analysis of the micorarray data. Methods: Our previous cDNA microarray experiments generated a large set of data that had 5652 genes significantly altered for at least one of eight time points in the mouse lacrimal gland after corneal injury. Here we employed the newest algorithms proposed by Tseng and Wong (Biometrics, in press) to perform cluster analysis of microarray data. This new algorithm is specifically designed for microarray studies to find core groups of co–regulated genes when a large number of genes are modulated. Results:The cluster analysis from our cDNA microarray data generated significant information regarding co–regulated gene groups in the lacrimal gland, which specifically related to corneal injury. Those altered genes were clustered in three different ways according to their expression profiles along the time course of 8 time points: 1)using all 8 time points (G1); 2) using the first 4 time points (G2); and 3) using the last 4 time points (G3). The results showed that 1205 genes in G1 formed 35 tight clusters (21 % of 5652 genes) and 811 genes in G2 formed 35 clusters (14 %) and 648 genes in G3 formed 37 clusters (11 %). The genes in G1 had 43 and 53 % overlap with G2 and G3, respectively. However, there were 46 and 57 % different genes between G2 and G3, indicating distinctive profiles of gene expression between the first 4 time points and the last 4 time points. Moreover, the clusters in every group showed unique patterns that differed substantially from one cluster to another. Conclusions: Our cluster analysis using the newest algorithms demonstrates the advantages of continuing algorithm development and reveals distinctive patterns of co–regulation in lacrimal gland gene expression following corneal injury.

Keywords: lacrimal gland • gene/expression • gene microarray 
×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×