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Genomic Locus Operation - DataBase

eagle-i ID


Resource Type

  1. Database


  1. Resource Description
    "Glo-DB is designed to perform position-based queries of genomic sequence annotations (features). It contains a query language that affords many different types of position searches via command line and graphical user interfaces, and incorporates various visualization tools. In this application, features are combined into sets, called "tracks," where a single track can contain features from any number of genomics sequences. For example, a track might contain all exons in a genome, the introns on a particular chromosome segment, etc. These feature sets can be loaded from different types of text files. Since features are just start and stop positions on a sequence, each feature can be viewed as a unique object located on the sequence or as a mask over the specified region of the sequence. Glo-DB's built-in operators will seamlessly manipulate features in either representation. For example, a user might be interested in the set of all exons on a chromosome that overlap with a specific set of genes on that same chromosome. In this case one track would contain the set of exons ("exon_track"), another the set of genes ("gene_track"). To find all overlapping features, the user would perform an "AND" operation on these two sets of features, returning a track containing the set of overlapping features ("exon_track AND gene_track"). If the user only wanted the exons in the output set, the genes could then be subtracted out ("((exon_track AND gene_track) sMINUS gene_track)"). Alternatively, a user could "subtract" the positions of the exons on a chromosome from the gene positions, to get a track containing a set of new features that represent the introns in the genes. Using tracks containing the exons ("exon_track") and genes ("gene_track"), the user would then negate the two ("gene_track - exon_track"), returning a set of new features encoding the positions within the genes not encoded by the exons. In the first example, the "set based" operators acted on the features as immutable position pairs allowing for the sets to be altered but not the features themselves. In the second example, the "binary" operator acted on the features as positions on the sequence, allowing for the features to be spliced and merged into new features."
  2. Additional Name
  3. Used by
    Kim Laboratory: Computational Evolutionary Biology
  4. Operating System
  5. Operating System
    Mac OS X
  6. Operating System
    Windows (2000 or later)
  7. Data Input
    Genomic feature sets
  8. Data Input
    DNA sequence
  9. Website(s)
  10. Related Technique
    Bioinformatics analysis
  11. Developed by
    Kim, Junhyong., PhD
  12. Developed by
    Fisher, Stephen., PhD
Provenance Metadata About This Resource Record
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  2. contributor
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Copyright © 2016 by the President and Fellows of Harvard College
The eagle-i Consortium is supported by NIH Grant #5U24RR029825-02 / Copyright 2016