Dataset Information

DAG expression: high-throughput gene expression analysis of real-time PCR data using standard curves for relative quantification.

ABSTRACT:

Background

Real-time quantitative PCR (qPCR) is still the gold-standard technique for gene-expression quantification. Recent technological advances of this method allow for the high-throughput gene-expression analysis, without the limitations of sample space and reagent used. However, non-commercial and user-friendly software for the management and analysis of these data is not available.

Results

The recently developed commercial microarrays allow for the drawing of standard curves of multiple assays using the same n-fold diluted samples. Data Analysis Gene (DAG) Expression software has been developed to perform high-throughput gene-expression data analysis using standard curves for relative quantification and one or multiple reference genes for sample normalization. We discuss the application of DAG Expression in the analysis of data from an experiment performed with Fluidigm technology, in which 48 genes and 115 samples were measured. Furthermore, the quality of our analysis was tested and compared with other available methods.

Conclusions

DAG Expression is a freely available software that permits the automated analysis and visualization of high-throughput qPCR. A detailed manual and a demo-experiment are provided within the DAG Expression software at http://www.dagexpression.com/dage.zip.

SUBMITTER: Ballester M

PROVIDER: S-EPMC3832397 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Publications

DAG expression: high-throughput gene expression analysis of real-time PCR data using standard curves for relative quantification.

Ballester María M Cordón Rubén R Folch Josep M JM

PloS one 20131118 11

<h4>Background</h4>Real-time quantitative PCR (qPCR) is still the gold-standard technique for gene-expression quantification. Recent technological advances of this method allow for the high-throughput gene-expression analysis, without the limitations of sample space and reagent used. However, non-commercial and user-friendly software for the management and analysis of these data is not available.<h4>Results</h4>The recently developed commercial microarrays allow for the drawing of standard curve ...[more]

PMID: 24260380

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Project description:BackgroundCurrently real time PCR is the most precise method by which to measure gene expression. The method generates a large amount of raw numerical data and processing may notably influence final results. The data processing is based either on standard curves or on PCR efficiency assessment. At the moment, the PCR efficiency approach is preferred in relative PCR whilst the standard curve is often used for absolute PCR. However, there are no barriers to employ standard curves for relative PCR. This article provides an implementation of the standard curve method and discusses its advantages and limitations in relative real time PCR.ResultsWe designed a procedure for data processing in relative real time PCR. The procedure completely avoids PCR efficiency assessment, minimizes operator involvement and provides a statistical assessment of intra-assay variation. The procedure includes the following steps. (I) Noise is filtered from raw fluorescence readings by smoothing, baseline subtraction and amplitude normalization. (II) The optimal threshold is selected automatically from regression parameters of the standard curve. (III) Crossing points (CPs) are derived directly from coordinates of points where the threshold line crosses fluorescence plots obtained after the noise filtering. (IV) The means and their variances are calculated for CPs in PCR replicas. (V) The final results are derived from the CPs' means. The CPs' variances are traced to results by the law of error propagation. A detailed description and analysis of this data processing is provided. The limitations associated with the use of parametric statistical methods and amplitude normalization are specifically analyzed and found fit to the routine laboratory practice. Different options are discussed for aggregation of data obtained from multiple reference genes.ConclusionA standard curve based procedure for PCR data processing has been compiled and validated. It illustrates that standard curve design remains a reliable and simple alternative to the PCR-efficiency based calculations in relative real time PCR.

Dataset Information

DAG expression: high-throughput gene expression analysis of real-time PCR data using standard curves for relative quantification.

Background

Results

Conclusions

Publications

DAG expression: high-throughput gene expression analysis of real-time PCR data using standard curves for relative quantification.

Similar Datasets

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