Gene Set Analyses for Microarray Experiments on Prokaryotic Organisms
Author Information
Author(s): Tintle Nathan L, Best Aaron A, DeJongh Matthew, Van Bruggen Dirk, Heffron Fred, Porwollik Steffen, Taylor Ronald C
Primary Institution: Hope College
Hypothesis
Can gene set analysis methods be effectively applied to microarray experiments with few replicates in prokaryotic organisms?
Conclusion
The MAXMEAN-NR method offers increased robustness and biological relevance in gene set analysis for prokaryotic experiments with few replicates.
Supporting Evidence
- MAXMEAN-NR maintains the nominal rate of false positive findings while offering good statistical power.
- Other methods like ABSSUM-NR and SUM-NR are powerful for smaller gene set sizes.
- MAXMEAN-NR can detect biologically relevant sets when other methods cannot.
Takeaway
This study looks at how to analyze gene data from bacteria when there aren't many samples, and finds a new method that works better than older ones.
Methodology
The study compares five non-cutoff based gene set analysis methods with Fisher's exact test using simulated and real data.
Potential Biases
The competitive null hypothesis may lead to underestimating the significance of gene sets with small but real mean log-ratios.
Limitations
The methods are based on gene sampling, which may lead to increased false positives in experiments with few regulated genes.
Digital Object Identifier (DOI)
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