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oPOSSUM: identification of over-represented transcription factor binding sites in co-expressed genes.

Targeted transcript profiling studies can identify sets of co-expressed genes; however, identification of the underlying functional mechanism(s) is a significant challenge. Established methods for the analysis of gene annotations, particularly those based on the Gene Ontology, can identify functional linkages between genes. Similar methods for the identification of over-represented transcription factor binding sites (TFBSs) have been successful in yeast, but extension to human genomics has largely proved ineffective. Creation of a system for the efficient identification of common regulatory mechanisms in a subset of co-expressed human genes promises to break a roadblock in functional genomics research. We have developed an integrated system that searches for evidence of co-regulation by one or more transcription factors (TFs). oPOSSUM combines a pre-computed database of conserved TFBSs in human and mouse promoters with statistical methods for identification of sites over-represented in a set of co-expressed genes. The algorithm successfully identified mediating TFs in control sets of tissue-specific genes and in sets of co-expressed genes from three transcript profiling studies. Simulation studies indicate that oPOSSUM produces few false positives using empirically defined thresholds and can tolerate up to 50% noise in a set of co-expressed genes.

Pubmed ID: 15933209


  • Ho Sui SJ
  • Mortimer JR
  • Arenillas DJ
  • Brumm J
  • Walsh CJ
  • Kennedy BP
  • Wasserman WW


Nucleic acids research

Publication Data

June 3, 2005

Associated Grants

  • Agency: Canadian Institutes of Health Research, Id: 64231

Mesh Terms

  • Algorithms
  • Animals
  • Binding Sites
  • Databases, Nucleic Acid
  • Gene Expression Profiling
  • Gene Expression Regulation
  • Humans
  • Internet
  • Mice
  • NF-kappa B
  • Oligonucleotide Array Sequence Analysis
  • Promoter Regions, Genetic
  • Transcription Factors