Validating microarray data using rt real time pcr

Filtering of microarray data for measures of quality (fold-change and ρ-value) proves to be the most critical factor, with significant correlations of ρτ;0.80 consistently observed when quality scores are applied.

by Caitlin Smith Microarrays, let researchers study changes in gene expression with vast numbers of samples in parallel, all on a tiny chip. But microarrays can also give results that vary considerably. Conventional wisdom is that a large change in gene expression reported by microarrays should be validated by an independent method.

While we are still far from establishing these guidelines, I believe that the community is working towards a more uniform method.” In the meantime, scientists must flesh out their own definitions, based on their own systems and experiments.

However, the reliability of the microarray results is being challenged due to the existence of different technologies and non-standard methods of data analysis and interpretation.In the absence of a "gold standard"/"reference method" for the gene expression measurements, studies evaluating and comparing the performance of various microarray platforms have often yielded subjective and conflicting conclusions.With either platform, 16 of 17 definitely regulated genes were correctly identified, and no definitely unregulated transcript was falsely identified as regulated.Accuracy of the fold-change measurements obtained with each platform was assessed by determining measurement bias.From there, we have used q RT-PCR to directly validate the gene expression using the same clinical tissue samples.

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We compared the accuracy of microarray measurements obtained with oligonucleotide arrays (Gene Chip, Affymetrix) with a laboratory-developed c DNA array by assaying test RNA samples from an experiment using a paradigm known to regulate many genes measured on both arrays.

We selected 47 genes represented on both arrays, including both known regulated and unregulated transcripts, and established reference relative expression measurements for these genes in the test RNA samples using quantitative reverse transcriptase real-time PCR (QRTPCR) assays.

For each platform, four technical replicates were performed on the same total RNA samples according to each manufacturer's standard protocols.

For Agilent arrays, comparative hybridization was performed using incorporation of Cy5 for brain/lung/liver RNA and Cy3 for UHR RNA (common reference).

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