Comparative Analysis of Microarray Technologies for Gene Expression in Diabetes Models
Author Information
Author(s): Wilder Steven P, Kaisaki Pamela J, Argoud Karène, Salhan Anita, Ragoussis Jiannis, Bihoreau Marie-Thérèse, Gauguier Dominique
Primary Institution: The Wellcome Trust Centre for Human Genetics, University of Oxford
Hypothesis
The study aims to assess the performance and reproducibility of gene expression data obtained from different microarray technologies in rat and mouse models of diabetes.
Conclusion
The study provides an extensive assessment of analytical methods best suited for processing data from different microarray technologies, aiding in the integration of diverse gene expression datasets.
Supporting Evidence
- The study found excellent agreement between data generated on the Affymetrix and Illumina platforms.
- The choice of Affymetrix signal extraction technique significantly affected the concordance across platforms.
- Quantitative Real Time Polymerase Chain Reaction (qRT-PCR) was used to verify results from the microarray platforms.
Takeaway
This study looked at how well different machines measure gene activity in rats and mice with diabetes, finding that some machines work better together than others.
Methodology
The study involved testing various microarray platforms (Affymetrix, Illumina, and Operon) to analyze gene expression data from rat and mouse models, focusing on the reproducibility and performance of these technologies.
Limitations
The study's findings may be limited by the specific strains of rats and mice used, as well as the number of genes tested.
Participant Demographics
The study involved male inbred strains of rats (Brown-Norway, Goto-Kakizaki, Wistar-Kyoto) and mice (C57BL/6J).
Digital Object Identifier (DOI)
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