The curse of normalization
2002
The Challenges of Normalizing Microarray Data
publication
Author Information
Author(s): Olaf Wolkenhauer, Carla Moller-Levet, Fatima Sanchez-Cabo
Primary Institution: UMIST, Manchester, UK
Conclusion
Normalization is essential for analyzing microarray data, but it can also reduce the informative content of the data.
Supporting Evidence
- Normalization helps to remove non-biological variation from microarray data.
- Different normalization methods can affect the interpretation of gene expression data.
- Close collaboration between biologists and data analysts is crucial for effective data analysis.
Takeaway
When scientists study genes using special technology, they have to clean up the data to make it useful, but this can sometimes make the data less clear.
Methodology
The review discusses various normalization methods for microarray data and their implications.
Limitations
The review does not cover all normalization methods and acknowledges that some approaches may not be suitable for all experiments.
Digital Object Identifier (DOI)
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