Selecting Control Genes for RT-QPCR Using Public Microarray Data
Author Information
Author(s): Vlad Popovici, Darlene R. Goldstein, Janine Antonov, Rolf Jaggi, Mauro Delorenzi, Pratyaksha Wirapati
Primary Institution: Swiss Institute of Bioinformatics
Hypothesis
Translating the list of candidate genes from microarray to PCR platform is feasible.
Conclusion
We proposed a new method for identifying candidate control genes for RT-QPCR which was able to rank thousands of genes according to some predefined suitability criteria and we applied it to the case of breast cancer.
Supporting Evidence
- The method allows the combination of multiple data sets from different platforms.
- Two new control genes for breast cancer were identified and validated by RT-QPCR.
- The approach is platform- and normalization-independent.
Takeaway
The study found a way to choose the best genes to use as controls in experiments that measure gene activity, which helps scientists get more accurate results.
Methodology
The study used publicly available microarray data to score and rank candidate genes for their suitability as control genes for RT-QPCR.
Limitations
The lists produced are not universally applicable as different pathologies may affect the control genes' effectiveness.
Participant Demographics
Breast cancer samples were used for the analysis.
Digital Object Identifier (DOI)
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