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Gene expression levels assessed by oligonucleotide microarray analysis and quantitative real-time RT-PCR - how well do they correlate?

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Gene expression levels assessed by oligonucleotide microarray analysis and quantitative real-time RT-PCR - how well do they correlate?

Gene expression levels assessed by oligonucleotide microarray analysis and quantitative real-time RT-PCR - how well do they correlate?
Peter B Dallas , Nicholas G Gottardo , Martin J Firth , Alex H Beesley , Katrin Hoffmann , Philippa A Terry , Joseph R Freitas , Joanne M Boag , Aaron J Cummings and Ursula R Kees

BMC Genomics 2005, 6:59     doi:10.

Category: BMC-Genomics

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Gene expression levels assessed by oligonucleotide microarray analysis and quantitative real-time RT-PCR - how well do they correlate?
Peter B Dallas , Nicholas G Gottardo , Martin J Firth , Alex H Beesley , Katrin Hoffmann , Philippa A Terry , Joseph R Freitas , Joanne M Boag , Aaron J Cummings and Ursula R Kees

BMC Genomics 2005, 6:59     doi:10.1186/1471-2164-6-59

Published   27 April 2005


Abstract (provisional)

Background The use of microarray technology to assess gene expression levels is now widespread in biology. The validation of microarray results using independent mRNA quantitation techniques remains a desirable element of any microarray experiment. To facilitate the comparison of microarray expression data between laboratories it is essential that validation methodologies be critically examined. We have assessed the correlation between expression scores obtained for 48 human genes using oligonucleotide microarrays and the expression levels for the same genes measured by quantitative real-time RT-PCR (qRT-PCR).

Results Correlations with qRT-PCR data were obtained using microarray data that were processed using robust multi-array analysis (RMA) and the MAS 5.0 algorithm. Our results indicate that when identical transcripts are targeted by the two methods, correlations between qRT-PCR and microarray data are generally strong (r [greater than or equal to] 0.89). However, we observed poor correlations between qRT-PCR and RMA or MAS 5.0 normalized microarray data for 13% or 16% of genes, respectively.

Conclusions These results highlight the complementarity of oligonucleotide microarray and qRT-PCR technologies for validation of gene expression measurements, while emphasizing the continuing requirement for caution in interpreting gene expression data.
 

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