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The utility of MAS5 expression summary and detection call algorithms
Stuart D Pepper1, Emma K Saunders, Laura E Edwards
1Cancer Research UK, Paterson Institute for Cancer Research, The University of Manchester, Christie Hospital Site, Withington, Manchester, UK. spepper@picr.man.ac.uk <spepper@picr.man.ac.uk>
BMC Bioinformatics
|August 1, 2007
Summary
The MicroArray Suite 5.0 (MAS5.0) algorithm, when used with detection calls, proves to be a sensitive and selective tool for identifying differentially expressed genes, addressing previous concerns about false positives.
Area of Science:
- Genomics
- Bioinformatics
- Molecular Biology
Background:
- The MAS5.0 algorithm for gene expression analysis has faced criticism for high false positive rates, particularly at low intensity signals.
- This limitation stems from exaggerated variance associated with low-intensity measurements.
Purpose of the Study:
- To evaluate the performance of the MAS5.0 algorithm when used in conjunction with detection calls.
- To determine if MAS5.0 can achieve both sensitivity and selectivity in identifying differentially expressed genes.
Main Methods:
- Utilized replicated cell line data for analysis.
- Compared MAS5.0 results with those from RMA and GCRMA algorithms.
- Validated findings using real-time PCR.
- Assessed performance on Latin square datasets.
Main Results:
- MAS5.0, when paired with detection calls, demonstrated both sensitivity and selectivity.
- Identified differentially expressed transcripts missed by RMA and GCRMA algorithms.
- Real-time PCR confirmed the expression changes detected by MAS5.0.
- Filtered MAS5.0 performance approached that of peer algorithms on standard datasets.
Conclusions:
- The MAS5.0 algorithm, when integrated with detection calls, is a reliable method for sensitive and selective identification of differentially expressed genes.
- This approach mitigates previous concerns regarding the algorithm's accuracy.
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