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Real Time RT-PCR

Real Time RT-PCR

Real-time reverse transcription-polymerase chain reaction, or Real-time RT-PCR, is an analytical tool used to determine the expression level of target genes. The method involves converting mRNA to complementary DNA with the help of an enzyme known as reverse transcriptase, followed by the PCR amplification of the cDNA. These two processes can be performed simultaneously in a single tube or separately as a two-step reaction.
The real-time quantification of the number of amplified products is...

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Updated: Jun 23, 2026

Profiling of Pre-micro RNAs and microRNAs using Quantitative Real-time PCR (qPCR) Arrays

Profiling of Pre-micro RNAs and microRNAs using Quantitative Real-time PCR (qPCR) Arrays

Published on: December 3, 2010

Evaluation of microarray preprocessing algorithms based on concordance with RT-PCR in clinical samples.

Balazs Gyorffy¹, Bela Molnar, Hermann Lage

¹Hungarian Academy of Sciences and Semmelweis University Budapest, Budapest, Hungary.

|May 23, 2009

Summary

This summary is machine-generated.

This study compared Affymetrix microarray preprocessing algorithms using RT-PCR as a reference. PLIER+16 showed the highest consistency with RT-PCR, supporting its use for clinical microarray data analysis.

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Last Updated: Jun 23, 2026

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Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

Numerous preprocessing algorithms exist for Affymetrix gene expression microarrays.
Previous evaluations focused on spike-in data, not real-world research samples.

Purpose of the Study:

To comprehensively compare preprocessing algorithms for Affymetrix microarrays using clinical research samples.
To evaluate algorithm accuracy against TaqMan RT-PCR as a reference standard.

Main Methods:

Utilized two experimental datasets: colon biopsies (84 genes, 36 samples) and cancer cell lines (75 genes, 29 samples).
Assessed gene expression consistency between Affymetrix microarrays and TaqMan RT-PCR using Pearson correlation.
Introduced log-ratio discrepancy as a novel metric for inter-platform discordance.

Main Results:

PLIER+16 preprocessing algorithm demonstrated the highest consistency with RT-PCR measurements across both datasets.
While PLIER+16 performed best, the performance differences among most tested algorithms were not statistically significant.
Log-ratio discrepancy provided a refined measure of discordance between gene expression platforms.

Conclusions:

PLIER+16 is a recommended preprocessing algorithm for clinical Affymetrix microarray data.
Other algorithms exhibited similar performance, suggesting they are also viable options.
The study provides valuable insights for selecting appropriate preprocessing methods in gene expression analysis.