Exploring relationships and mining data with the UCSC Gene Sorter

  1. W.J. Kent2,
  2. Fan Hsu2,
  3. Donna Karolchik2,3,
  4. Robert M. Kuhn2,
  5. Hiram Clawson2,
  6. Heather Trumbower2, and
  7. David Haussler1
  1. 1 Howard Hughes Medical Institute, University of California, Santa Cruz, California 95064, USA
  2. 2 Center for Biomolecular Science and Engineering, University of California, Santa Cruz, California 95064, USA

Abstract

In parallel with the human genome sequencing and assembly effort, many tools have been developed to examine the structure and function of the human gene set. The University of California Santa Cruz (UCSC) Gene Sorter has been created as a gene-based counterpart to the chromosome-oriented UCSC Genome Browser to facilitate the study of gene function and evolution. This simple, but powerful tool provides a graphical display of related genes that can be sorted and filtered based on a variety of criteria. Genes may be ordered based on such characteristics as expression profiles, proximity in genome, shared Gene Ontology (GO) terms, and protein similarity. The display can be restricted to a gene set meeting a specific set of constraints by filtering on expression levels, gene name or ID, chromosomal position, and so on. The default set of information for each gene entry—gene name, selected expression data, a BLASTP E-value, genomic position, and a description—can be configured to include many other types of data, including expanded expression data, related accession numbers and IDs, orthologs in other species, GO terms, and much more. The Gene Sorter, a CGI-based Web application written in C with a MySQL database, is tightly integrated with the other applications in the UCSC Genome Browser suite. Available on a selected subset of the genome assemblies found in the Genome Browser, it further enhances the usefulness of the UCSC tool set in interactive genomic exploration and analysis.

Footnotes

  • [Supplemental material is available online at www.genome.org.]

  • Article and publication are at http://www.genome.org/cgi/doi/10.1101/gr.3694705.

  • 3 Corresponding author. E-mail donnak{at}soe.ucsc.edu; fax (775) 703-6375.

    • Accepted February 23, 2005.
    • Received January 12, 2005.
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