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This article in CS

  1. Vol. 46 No. 5, p. 1998-2007
    Received: Mar 8, 2006

    * Corresponding author(s): agingle@uga.edu
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An Integrated Web Resource for Cotton

  1. Alan R. Gingle *a,
  2. Hongyu Yanga,
  3. Peng W. Cheeb,
  4. O. Lloyd Mayb,
  5. Junkang Ronga,
  6. Daryl T. Bowmanc,
  7. Edward L. Lubbersb,
  8. J. LaDon Dayd and
  9. Andrew H. Patersona
  1. a Center for Applied Genetic Technologies, Univ. of Georgia, 111 Riverbend Rd., Athens, GA 30602
    b Dep. of Crop and Soil Sciences, Univ. of Georgia, Coastal Plain Experiment Station, Tifton, GA 31793
    c College of Agriculture and Life Sciences, North Carolina State Univ., Raleigh, NC 27695-8604
    d Dep. of Crop and Soil Sciences, The Univ. of Georgia, Georgia Station, Griffin Campus, Griffin, GA 30223


“The Cotton Diversity Database” (http://cotton.agtec.uga.edu) is a Web resource for cotton (Gossypium spp.) phenotypic and genomic data. A primary goal for this resource is to provide both a useful management tool for breeders and other applied scientists and a research tool for genetic and genomic scientists. The resource contains four interface suites that include displays for each of the available phenotypic or genomic data types. These display suites are accessible via the genotype portal, a search interface that allows users to begin with a cotton accession and obtain all available data. The phenotypic data displays include graphical views of overall cultivar performance with means and between group standard deviations indicated in an easy-to-interpret graphical manner for common trial measures such as lint yield, micronaire, etc. The genomic data displays include interactive graphical views of genetic map and diversity data types. Genetic map data is displayed in both traditional linear and two-dimensional comparative dot plot formats. Genetic diversity data is displayed in an interactive tree-based format showing degrees of similarity among genotypes. The data are stored in Oracle relational database (RDBMS) schemas containing tables and views for data storage, auto-calculated statistics and display parameters. The searchable RDBMS provides flexibility for a wide range of query and search options as well as integration paths amongst the various data types.

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Copyright © 2006. Crop Science Society of AmericaCrop Science Society of America