qPCR techniques and analysis software tools

Quantitative real-time polymerase chain reaction (qPCR) is widely used for the detection of specific nucleic acids, measurement of RNA transcript abundance and validation of high-throughput experimental results. While high-throughput sequencing (HTS) has revolutionized the fields of genomics and transcriptomics, qPCR techniques have evolved and can now be performed in a high-throughput fashion.

What use for qPCR?

qPCR is an easy-to-perform technique to evaluate the relative (or absolute) expression of genes as compared to each other and/or a reference. Traditional qPCR is often used to validate results from gene arrays or HTS, as it is more precise, rapid to perform, and cheap.


Recently, new technologies have been developed to increase the number of genes that can be tested simultaneously. Next generation qPCR platforms use nanofluid systems to target up to thousands of genes per sample (Devonshire et al.).

Conventional and High-throughput qPCR


While conventional qPCR is still widely used in biology labs, current studies in transcriptomics evaluate the expression of thousands of genes at a time, and confirming the data using conventional qPCR can be difficult. Here is an overview of current technologies in high-throughput qPCR:


  • Fluidigm Biomark HD


The Biomark HD is a microfluid chips system that automates PCR reactions in nanoliter volume. This platform performs qPCR on either 48 or 96 different cDNA samples and can interrogate 48 or 96 genes on each of these samples. With this technology the BioMark instrument is capable of conducting qPCR, SNP genotyping, and digital PCR assays in a high-throughput, low volume fluidics chip.


  • The SmartChip Real-Time PCR System


A complete system that enables high-throughput, high-density, real-time PCR for gene expression or single nucleotide polymorphism (SNP) genotyping analysis. The SmartChip has 5.184 nanowells for a maximum of 1.728 gene targets per sample.


  • OpenArray


OpenArray technology uses a microscope slide–sized plate with 3,072 through-holes. Each plate contains 48 subarrays, each with 64 through-holes. Each through-hole is 300 μm in diameter and 300 μm deep and is treated with hydrophilic and hydrophobic coatings. Reagents are retained in the through-holes via surface tension (see Figure). One OpenArray plate can hold as many samples as can eight traditional 384-well plates.


  • QX200 Droplet Digital  PCR System


This platform couples individual emulsion vesicles formed by water-in-oil emulsion to a capillary-based analysis system. This provides absolute quantification of target DNA or RNA molecules for EvaGreen or probe-based digital PCR applications.

After PCR on a thermal cycler, droplets from each sample are analyzed individually on the QX200 Droplet Reader. Droplets are read well by well as they are streamed single file past a two-color optical detection system in a serial manner. Up to 96 samples can be processed per run. The PCR-positive and PCR-negative droplets are counted to provide absolute quantification of target DNA in digital form. Alternatively, amplified products can be extracted from droplets following PCR for downstream applications, such as sequencing or cloning.


Main steps and tools for analyzing qPCR data


qPCR data analysis can be boiled down to four main steps: Relative quantification, normalization, data visualization and statistical significance testing for Ct values between features (Figure 1).


Flow chart of qPCR data analysis
Flow chart of qPCR data analysis. From Pabinger et al.


qPCR analysis tools are often provided by the platforms to suit their specifications. Nonetheless, a number of software tools remain useful for different steps of the qPCR experiment.


  • Primer design: An obligatory first step in qPCR experiments is the design of primers. There are several parameters to play with in primer design, such as G and C base content, melting temperature, amplicon size, etc. Top software: Primer3, MRPrimerW, FastPCR, Primer-BLAST.


  • Normalization: In relative quantification, internal reference genes are used to determine fold-differences in expression of target genes. Top software: EasyQPCR, qpcrNorm, NormqPCR, normalyzer.


  • Data analysis: Data analysis in qPCR mainly consists in obtaining Ct values for each gene, normalizing values to a reference gene and then between conditions (Ct method). Top software: qpcR, NormqPCR, qbase+, monocle (for single-cell qPCR).


  • Multi-tasking tool: HTqPCR is a multi-tasking tool that performs quality assessment, normalization, data visualization and statistical significance testing for Ct values.



Pabinger et al. (2014). A survey of tools for the analysis of quantitative PCR (qPCR) data. Biomolecular Detection and Quantification.

Devonshire et al. (2013). Application of next generation qPCR and sequencing platforms to mRNA biomarker analysis. Methods.