Improving P Value Distribution in Microarray Analysis
Author Information
Author(s): Anthony A Fodor, Timothy L Tickle, Christine Richardson
Primary Institution: The University of North Carolina at Charlotte
Hypothesis
Can we achieve a uniform distribution of P values for non-differentially expressed genes in microarray experiments?
Conclusion
The study demonstrates a method that produces P values closer to a uniform distribution for non-differentially expressed genes.
Supporting Evidence
- The method demonstrated improves the reliability of P values in microarray analysis.
- The study highlights the importance of proper normalization techniques.
- Results indicate that traditional methods may produce misleading P values.
Takeaway
This study shows a way to make sure that the P values we get from gene tests are more reliable and not misleading.
Methodology
The study uses a technique to control false-positive rates by ensuring that P values for non-differentially expressed genes follow a uniform distribution.
Potential Biases
Potential biases from cross-hybridization and imperfect normalization could affect results.
Limitations
The study primarily focuses on a specific dataset and may not generalize to all microarray experiments.
Statistical Information
P-Value
p<0.05
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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