GO Trimming: Reducing Redundancy in Gene Ontology Datasets
Author Information
Author(s): Jantzen Stuart G, Sutherland Ben JG, Minkley David R, Koop Ben F
Primary Institution: Department of Biology & Centre for Biomedical Research, University of Victoria
Hypothesis
Can a systematic method be developed to reduce redundancy in Gene Ontology datasets?
Conclusion
The GO Trimming method effectively reduces redundancy in Gene Ontology lists, making them more manageable and informative.
Supporting Evidence
- The GO Trimming method reduced an initial list of 90 terms to 54 by eliminating 36 redundant terms.
- GO Trimming performs well compared to existing methods for reducing redundancy in Gene Ontology datasets.
- The method is designed to be simple and systematic, making it easy to integrate into research workflows.
Takeaway
This study introduces a method called GO Trimming that helps scientists make sense of long lists of gene functions by removing repeated information.
Methodology
The GO Trimming method uses an algorithm to identify and remove redundant terms from enriched Gene Ontology lists based on hierarchical relationships.
Limitations
The method does not address false positives and is independent of multiple testing corrections.
Statistical Information
P-Value
0.00338
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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