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Estimating the annotation error rate of curated GO database sequence annotations.

Craig E Jones1, Alfred L Brown, Ute Baumann

  • 1School of Computer Science, University of Adelaide, South Australia, Australia. craig@cs.adelaide.edu.au

BMC Bioinformatics
|May 24, 2007
PubMed
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The Gene Ontology (GO) sequence database has an estimated 28-30% error rate. Sequence similarity-based annotations (ISS) show a higher error rate (49%) and should be used cautiously.

Area of Science:

  • Bioinformatics
  • Genomics
  • Data Quality Assessment

Background:

  • Sequence function annotations are crucial for biological research and computational analysis.
  • Data quality of these annotations has been under-investigated.
  • The Gene Ontology (GO) is a primary resource for functional sequence annotations.

Purpose of the Study:

  • To develop a novel method for estimating the error rate of curated sequence function annotations.
  • To assess the data quality of annotations within the GO sequence database (GOSeqLite).

Main Methods:

  • Artificially introduced errors into sequence annotations at controlled rates.
  • Employed regression modeling to analyze the impact of errors on annotation precision.
  • Focused on annotations derived from BLAST sequence similarity searches.

Related Experiment Videos

Main Results:

  • The overall error rate for curated GO sequence annotations was estimated between 28% and 30%.
  • Annotations not relying on sequence similarity (non-ISS) had lower error rates (13-18%).
  • Annotations utilizing sequence similarity (ISS) exhibited significantly higher error rates (49%).

Conclusions:

  • While overall GO annotation quality is high, ISS annotations warrant caution due to elevated error rates.
  • Systems using ISS annotations for prediction may experience higher false positive rates.
  • Curators should carefully review ISS annotations; users can generally trust GO database annotations.