Correcting Scaling Mismatches in Microarray Data
Author Information
Author(s): Barenco Martino, Stark Jaroslav, Brewer Daniel, Tomescu Daniela, Callard Robin, Hubank Michael
Primary Institution: Institute of Child Health, University College London, UK
Hypothesis
Can a set of constant genes be used to correct scaling mismatches in microarray data?
Conclusion
The proposed method can effectively correct scaling mismatches in microarray data by using a set of constant genes.
Supporting Evidence
- The algorithm was tested on both artificial and real experimental data.
- The method showed that constant genes can be reused across different experiments.
- Rescaling improved the accuracy of gene expression measurements.
Takeaway
This study shows how to fix problems in gene data from experiments so that scientists can understand the results better.
Methodology
The study used a recursive algorithm to identify constant genes and rescale microarray signals.
Limitations
The method relies on the assumption that a sufficient number of constant genes exist across experiments.
Digital Object Identifier (DOI)
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