Real-Time PCR Data Analysis

Real-time PCR has become a widely used technique for a variety of applications, such as gene expression, mutational analysis, and pathogen detection. Many biotechnology companies offer real-time PCR instruments with data analysis software packages to assist with these applications. However, some software packages are easier to use than others, and some offer more features, such as multiple chart/table view and quality control (QC) flags to help enhance the data analysis experience. In this section we give an overview of Bio-Rad's CFX Maestro™ Software features including high resolution melt (HRM) analysis capabilities.

Related Topics: qPCR Instrumentation, qPCR Reagents, qPCR Assay Design and Optimization, Real-Time PCR Experimental Design, MIQE and RDML Guidelines, PCR Troubleshooting, High Resolution Melting and PCR Primer and Probes Chemistries.

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CFX Maestro Software Features

All of Bio-Rad's real-time PCR detection systems include the powerful, easy-to-use CFX Maestro Software. With one software for all four systems, you can easily open and read files from any of the instruments, collaborate with other researchers, and move to another system without learning to use new software.

Similar to other real-time PCR software, CFX Maestro software offers several analysis modules, including quantification, melt curve, gene expression, allelic discrimination, and end-point analyses. An example of how to analyze a gene expression experiment in CFX Maestro software is shown below.

Set up the plate — indicate position of unknown, no template controls (NTCs), and standard curve samples on plate (Figure 1). This can be done before, during, or after a run.

Fig. 1. Plate setup in the Plate Editor window.

Fig. 1. Plate setup in the Plate Editor window.

Analyze the data — a data file is automatically generated after a run with the gene expression module. Easily view up to six different charts or tables, such as the amplification plot, standard curve, gene expression chart, plate layout, or melt peak with the Custom Data View tab (Figure 2). Check the efficiency and R2 of the standard curve. The efficiency should be within 90–110% and the R2 should be >0.990. If these values are out of range, you will need to troubleshoot your experiment.

Fig. 2. Custom Data View window.

Fig. 2. Custom Data View window.

Export results for publication — Quickly export any charts or tables by right clicking in the window and selecting Save Image As (Figure 3) or Export to Excel (Figure 4). You can also create reports or real-time PCR data markup language (RDML) files for quick import into qbase+ software.

Fig. 4. Select Save Image As in the data analysis window. Fig. 3. Select Export to Excel in the data analysis window.
 

Fig. 3. Select Save Image As in the data analysis window.

 

Fig. 4. Select Export to Excel in the data analysis window.

 
High Resolution Melt (HRM) Analysis

In addition to the typical software packages, some instruments also offer HRM software to genotype samples based on their DNA thermal denaturation properties. HRM analysis requires careful experimental design, HRM-specific reagents, and a sensitive real-time PCR instrument with software that can handle large quantities of data. HRM software is usually straightforward, and should allow users to:

  • Compare and combine data from multiple experiments by combining run results into a single melt study
  • Display a plate view for easy identification of sample genotypes
  • Share analysis settings among experiments
  • Analyze multiple experiments from a single plate
  • View all charts in a single window for simplified data analysis and interpretation

An example of analyzing HRM data using Bio-Rad's HRM software, Precision Melt Analysis™ software, is shown below. In this example, Precision Melt Analysis software is used to discriminate between SNP genotypes (C to T substitution). The software uses the default analysis settings to assign a cluster to each sample. A normalized melt curve and a difference curve are generated for each well. These profiles can then be used to determine the different genotypes.

Melt Curve.

Normalized Melt curve.

Difference Curve.

Difference curve.