Improving Gene Set Enrichment Assessment
Author Information
Author(s): Alex Lewin, Ian C Grieve
Primary Institution: Imperial College London
Hypothesis
Can grouping Gene Ontology terms improve the assessment of gene set enrichment in microarray data?
Conclusion
Grouping Gene Ontology terms improves the interpretation of gene set enrichment for microarray data.
Supporting Evidence
- The method found groups of GO terms significantly over-represented amongst differentially expressed genes.
- Three groups were found significant after controlling for false discovery rate at 5%.
- The study applied the method to three different data sets, demonstrating its versatility.
Takeaway
This study shows that by grouping related gene terms together, scientists can better understand how genes are affected in different conditions.
Methodology
The study used the POSOC software to group Gene Ontology terms and performed statistical tests to assess their significance among differentially expressed genes.
Limitations
The method may retain a considerable amount of dependence between groups, which could affect the results.
Statistical Information
P-Value
0.006
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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