Abstract
Although gene expression microarray data analysis has been developed and used during the last 15 years, microRNA (miRNA) analysis is still under development and important aspects affecting the final results such as normalization still remain unclear. In this work we have studied and compared the effect of non normalization and four different normalization strategies (75th percentile, hsa-mir103 and hsa-mir-let7a control based and median of all expressed miRNA) on a data set of colon cancer miRNA microarrays. Different subsets of samples were used to study normalization effects comparing data distributions before and after normalization with the different strategies. Median of expressed miRNA behaved the best among the normalizations studied. Class comparison based analysis showed that differentially expressed miRNA are highly dependent on the normalization techniques applied.
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López-Campos, G.H., Romera-López, A., Martín-Sánchez, F., Diaz-Rubio, E., López-Alomso, V., Pérez-Villamil, B. (2011). MicroRNA Microarray Data Analysis in Colon Cancer: Effects of Normalization. In: Cabestany, J., Rojas, I., Joya, G. (eds) Advances in Computational Intelligence. IWANN 2011. Lecture Notes in Computer Science, vol 6692. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21498-1_33
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DOI: https://doi.org/10.1007/978-3-642-21498-1_33
Publisher Name: Springer, Berlin, Heidelberg
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