@article {bioinflmu-404,
	title = {{Normalization strategies for mRNA expression data in cartilage research}},
	journal = {Osteoarthritis Cartilage},
	volume = {16},
	year = {2008},
	pages = {947-955},
	abstract = {OBJECTIVE: Normalization of mRNA data, i.e., the calculation of mRNA
expression values comparable in between different experiments, is a major issue
in biomedical and orthopaedic/rheumatology research, both for single-gene
technologies [Northern blotting, conventional and quantitative polymerase chain
reaction (qPCR)] and large-scale gene expression experiments. In this study, we
tested several established normalization methods for their effects on gene
expression measurements. METHOD: Five standard normalization strategies were
applied on a previously published data set comparing peripheral and central late
stage osteoarthritic cartilage samples. RESULTS: The different normalization
procedures had profound effects on the distribution as well as the significance
values of the gene expression levels. All applied normalization procedures,
except the median absolute deviation scaling, showed a bias towards up- or
down-regulation of genes as visualized in volcano plots. Of interest, the
P-values were much more depending on the normalization procedure than the fold
changes. Ten commonly used housekeeping genes showed a significant variability in
between the different specimens investigated. The gene expression analysis by
cDNA arrays was confirmed for these genes by qPCR. CONCLUSION: This study
documents how much normalization strategies influence the outcome of gene
expression profiling analysis (i.e., the detection of regulated genes). Different
normalization approaches can significantly change the P-values and fold changes
of a large number of genes. Thus, it is of vital importance to check every
individual step of gene expression data analysis for its appropriateness. The use
of global robustness and quality measures for analyzing individual outcomes can
help in estimating the reliability of final microarray study results.},
	doi = {10.1016/j.joca.2007.12.007},
	author = {Katrin Fundel and Jochen Haag and Pia M. Gebhard and Ralf Zimmer and Thomas Aigner}
}