ModuleDigger: A Tool for Finding Regulatory Modules in Genes
Author Information
Author(s): Sun Hong, De Bie Tijl, Storms Valerie, Fu Qiang, Dhollander Thomas, Lemmens Karen, Verstuyf Annemieke, De Moor Bart, Marchal Kathleen
Primary Institution: Katholieke Universiteit Leuven
Hypothesis
Can itemset mining improve the detection of cis-regulatory modules in large gene datasets?
Conclusion
The itemset mining approach effectively prioritizes biologically valid cis-regulatory modules in large datasets.
Supporting Evidence
- ModuleDigger was tested on a benchmark dataset derived from a ChIP-Chip analysis.
- The method was compared with other cis-regulatory module detection tools.
- The results showed that ModuleDigger consistently identified biologically valid modules.
Takeaway
This study created a tool called ModuleDigger that helps scientists find important parts of DNA that control gene activity by looking at many genes at once.
Methodology
The study used itemset mining to detect cis-regulatory modules by analyzing transcription factor binding sites in a set of coexpressed genes.
Potential Biases
The reliance on specific datasets may introduce bias in the detection of modules.
Limitations
The method may overestimate the number of biologically valid modules due to conservative assumptions.
Statistical Information
P-Value
p<0.05
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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