dPCR and qPCR assays trusted by scientists worldwide

A good assay gives you results you can rely on – clear, reproducible and biologically meaningful, no matter what type of sample you're working with. The most important factors are specificity, sensitivity, efficiency and reproducibility.

Specificity ensures you're amplifying only the target you care about, not unrelated sequences that could skew your results. Sensitivity matters when you're detecting a rare target, like low-level viral RNA or a rare mutation. Reproducibility means you can trust your results across different experiments, instruments and users.

Efficiency, ideally between 90–110%, reflects how well the PCR amplifies the target with each cycle (with 100% meaning a perfect doubling of product each round). This is essential for accurate quantification in qPCR, where even small efficiency differences can distort your results. In dPCR, efficiency has less impact on quantification because each target is amplified independently to a detectable endpoint – but robust amplification still supports reliable detection and assay performance.

At QIAGEN, we design every assay with these principles in mind. We combine advanced bioinformatics, wet-lab testing and optimized reaction chemistry to create assays that perform right from the start – so you can focus on your research, not troubleshooting. 

These design principles align with the MIQE and dMIQE guidelines for best practices in qPCR and dPCR (1-3). QIAGEN has also codified many of these best practices in a white paper based on lessons learned from designing assays for over 14,000 human genes (4).

Specificity is what makes your results meaningful. If your assay amplifies the wrong sequence – even just once – it can throw off your entire experiment. That’s especially true in applications like liquid biopsy, where detecting a rare cancer mutation involves differentiating it from a sea of wild-type DNA. Specificity is also important in infectious disease research, where a false-positive from cross-reactivity could lead to misleading conclusions.

To get that level of specificity, we optimize every aspect of primer and probe design. That includes avoiding regions with known SNPs and minimizing off-target binding. For applications that demand even greater discrimination – like microRNA analysis – we use Locked Nucleic Acid (LNA) technology in select assays to improve binding strength and sequence selectivity. And for select assays used in critical applications, our wet-lab testing provides an added layer of specificity verification beyond in silico design

The more specific your assay, the more you can trust what it tells you – whether you're profiling tumor biomarkers, identifying microbes or detecting a viral genotype.

Sensitivity is what lets you see what might be otherwise missed. If your assay can’t detect low-abundance targets, you risk overlooking the very signals your research depends on – whether it's a rare mutation, a trace viral load or a pathogen hiding in a food sample.

This matters most in applications like liquid biopsy, where circulating tumor DNA can be present at extremely low levels. Or in antibiotic resistance surveillance, where detecting just a few copies of genes like mecA or blaKPC can help identify emerging threats early.

We design our assays for high sensitivity from the start – with short amplicons, optimized chemistry and, in the case of dPCR, sample partitioning that helps separate signal from noise. If you're working with degraded DNA, low-input RNA or other tough samples, that extra sensitivity can be the difference between detecting a rare target and missing it entirely.

Assay efficiency directly influences the accuracy of target quantification, especially in qPCR. Ideally, a qPCR assay should double the amount of DNA with each cycle – this is 100% efficiency. However, minor variations are common due to the biological nature of PCR. Efficiencies significantly below this ideal can lead to underestimation of your target, while efficiencies well above it may indicate non-specific amplification or primer-dimer formation, potentially inflating your results.

In gene expression studies, such efficiency deviations can distort fold-change calculations, leading to misinterpretations. In pathogen detection, they might result in missed low-level infections.

In dPCR, efficiency is less critical for quantification because each target molecule is amplified independently in isolated partitions and scored based on end-point detection. Even with suboptimal efficiency, as long as amplification occurs reliably within the partition, the result is still accurate. However, poor efficiency may reduce the fraction of positive partitions, impacting sensitivity – especially at low target concentrations.

At QIAGEN, we focus on optimizing assay design and reaction conditions to promote reliable and reproducible quantification across various applications and sample types. This systematic approach is also described in our white paper outlining key design insights from qPCR assays developed for more than 14,000 human genes (4).

Reproducibility is what makes your results reliable – not just once, but across runs, instruments and labs. Reproducibility depends on many factors, including sample quality, reaction setup and instrument calibration. Even small variations can impact quantification, especially in sensitive applications.

In clinical research, reproducibility is critical for validating biomarker assays before they can be trusted in diagnostic workflows. In agriculture or environmental testing, consistent results are essential for regulatory reporting and risk assessment.

At QIAGEN, we focus on assay design that supports reproducibility from the start. We use advanced bioinformatics to optimize primer and probe placement and conduct wet-lab verification for select assay groups in key research areas like oncology, infectious disease and microbiome analysis. By standardizing assay design and validating across diverse sample types, we aim to reduce technical variability and support consistent, high-quality results in real-world research settings.

With over 40 million predesigned dPCR and qPCR assays in our portfolio, finding the right one can feel overwhelming. The GeneGlobe assay wizard helps make that process easier by guiding you to the best-matched predesigned assay based on your research focus.

The assay wizard filters the options according to your target, species, application and preferred detection chemistry. So, instead of sifting through everything yourself, you get a short list of assays that fit what you’re working on. If no predesigned assay is available, the wizard connects you directly to the relevant custom design tool. It's a practical way to narrow down the options and select with confidence.

If your target isn’t covered by one of our predesigned qPCR or dPCR assays, you can easily create a custom one using the GeneGlobe custom design tools. These tools use the same advanced bioinformatics pipelines behind our predesigned assays, so you can generate high-quality designs quickly and easily, even for difficult or novel sequences. 

qPCR panels are a good choice when you want to study multiple genes or targets that are biologically related, such as those involved in the same pathway, disease area or regulatory process. Panels save time by bringing together relevant assays in a single, ready-to-use format. Individual assays are ideal when you're focused on just one or two targets.

Not sure where to start? The GeneGlobe panel finder can help. Just enter the targets you're interested in, and the panel finder shows relevant predesigned panels and how well they match what you're looking for. Plus, many of our predesigned panels can be further customized. You can easily swap out the targets you don’t need and replace them with ones that are more relevant, giving you the flexibility to fine-tune your panel without having to build a new one from scratch.

You can analyze your qPCR data using our complimentary, web-based tools in the GeneGlobe Data Analysis Center. Whether you're working with a single assay or an entire panel, the platform guides you step-by-step from sample management to tabular and graphical results, so you can go from Cq values to a publication-ready report with confidence.

The gene and miRNA expression analysis applications support commonly used methods like ΔΔCq fold-change calculation, normalization to multiple reference genes, and quality control checks for reverse transcription and PCR efficiency, as well as gDNA contamination. You’ll also get publication-ready charts and graphs, including volcano plots, scatter plots, heatmaps, and summary tables, which you can download as images or Excel files.

We also provide tools for mutation and microbial analysis. The qPCR mutation application reports whether the targeted sequence is wild type (WT) or mutated, while the microbial analysis resource indicates whether target organisms were detected and provides their relative abundance. Both also include quality control checks for PCR efficiency and annotate your results with the targets of cataloged panels.

Whether you're new to qPCR or just looking for a simpler way to handle your results, the GeneGlobe analysis applications are designed to support you at every step – no special software or bioinformatics expertise needed.

The right assay depends on your research question, target sequence and the type of analysis you need. If you're studying gene expression, you'll want a specific and efficient assay that delivers accurate quantification across a broad dynamic range. For mutation detection or pathogen identification, specificity becomes even more important, especially when your target is highly similar to other sequences.

Digital PCR is especially useful when you're working with low-abundance targets or you need absolute quantification, like in rare allele detection or copy number variation studies.

QIAGEN offers a broad portfolio of predesigned and custom assays for DNA, RNA and miRNA targets. Our assay wizard helps you sort by target, detection chemistry and application, so you can quickly find the assay that fits your experiment.

When you search for an assay in GeneGlobe, you may see multiple QuantiNova LNA PCR Assays (or Probe PCR Assays) available for the same target. That’s because these assays are optimized for different research goals, and choosing the right one depends on what you want to analyze.

• If you’re interested in broad transcript detection and want to know whether the gene of interest is expressed in your sample, the assay marked as “Best coverage” is your best choice. This gene-covering assay is designed to capture the most transcripts of the gene, making it ideal for general screening or when you don’t need to differentiate between isoforms.
• If you want to focus on a specific transcript, choose the assay labeled “Best transcript assay.” This option is optimized to detect the transcript of interest with high specificity, targeting the most relevant isoforms of that transcript. It’s well-suited for pathway analysis or targeted expression studies where precise quantification of one transcript matters.
• For experiments that require isoform-level resolution, such as studying alternative splicing, look for the assay marked “Best transcript-specific assay.” This assay is splice variant–specific, meaning it’s designed to detect only a single isoform. Use this when you need to differentiate between specific isoforms of a transcript.

Controls are essential for making sure your results are accurate, reproducible and meaningful. They help you catch issues like contamination, sample prep problems or reaction failures before they affect your data. The MIQE guidelines (1) outline key controls that should be part of every well-designed qPCR experiment, including:

• No-template control (NTC): Confirms that your reaction mix isn’t contaminated and that any amplification specifically arose from your samples.
• No-reverse transcription control (NRTC): Used in RNA and miRNA expression experiments to check for genomic DNA contamination by omitting the reverse transcription enzyme.
• Positive control: A known sample that contains the target sequence, so you know the assay is working as expected.
• Internal reference gene: Often called a housekeeping gene, this control is used in qPCR to normalize gene expression data and account for variation in input amount.

Including the right controls helps detect contamination, amplification errors or sample preparation inconsistencies, giving you confidence in your results. QIAGEN offers validated control assays and reference standards to support reliable experimental design.

Just like in qPCR, the right controls in dPCR help you catch issues early and trust your results. But because dPCR is often used for rare targets or low-abundance detection, some controls become even more important. According to the dMIQE 2020 guidelines (3), the most important controls include:

• No-template control (NTC): This is a reaction with no sample input – usually water instead – to make sure any amplification isn’t due to reaction mix contamination and only arose from your samples.
• Matrix-matched negative control: This control contains the same background matrix as your test sample but no target. It helps detect non-specific signals from complex sample types.
• Positive control: A sample that includes the target you’re trying to detect. It shows that your assay and reagents are working as expected.
• Internal positive control: Added to the same reaction as your test sample. This verifies the amplification process is working and can help flag inhibitors.
• Optional calibrators: These aren’t required for absolute quantification, but they can be useful for checking sample prep efficiency or comparing runs.

Together, these controls help ensure your dPCR results are as accurate and reproducible as the technology is capable of – even when working at the limits of detection.

Some targets (such as short sequences, closely related isoforms or regions with tricky base compositions) are simply harder to work with. That’s where Locked Nucleic Acid (LNA) technology comes in. LNA bases increase binding strength and stability, which helps improve both sensitivity and specificity for a variety of applications (5-7).

This added performance is especially helpful in applications like miRNA detection, where targets are short and highly similar, or SNP genotyping, where distinguishing between alleles requires sharp discrimination. It also improves performance in GC-rich regions, where standard primers can struggle to bind reliably.

QIAGEN incorporates LNA technology into select assays – including our QuantiNova LNA PCR and miRCURY LNA miRNA PCR portfolios – to help you get clear, confident results in these more challenging situations.

Both SYBR^® Green and hydrolysis probes are reliable ways to detect amplification in qPCR, but they serve different needs. SYBR^® Green binds to any double-stranded DNA, which means it detects everything that’s amplified – including non-specific products like primer-dimers. That makes it best for simpler, well-optimized experiments where you’re looking at a few known targets and cost or throughput is a concern. It’s widely used in routine gene expression studies and initial screens, where you can confirm specificity with a melt curve analysis.

Hydrolysis probes, like those used in TaqMan^® assays, only generate a signal when the probe binds to its target and is cleaved during amplification. That extra layer of specificity makes them ideal for applications where accuracy really matters – like SNP genotyping, rare mutation detection, microbial identification or multiplexed reactions, where you need clean, target-specific signals. Probes are more expensive and require more design up front, but they’re also more versatile and less prone to ambiguity in complex setups.

QIAGEN offers both SYBR^® Green and hydrolysis probe-based assays, allowing you to choose the best detection chemistry for your experiment while ensuring high sensitivity and specificity.

For a detailed review of real-time PCR detection chemistries, see the article by Navarro and colleagues (8).

Multiplexing lets you detect multiple targets in the same reaction by assigning each one a unique fluorescent signal. Multiplexing saves time, reduces sample usage and helps you compare targets under the exact same reaction conditions.

In qPCR, multiplexing is typically used when you're measuring gene expression of multiple transcripts, screening for pathogens or combining target and reference genes into a single reaction. It requires hydrolysis probes, since SYBR^® Green can’t distinguish between different targets in the same tube. However, as the number of targets increases, so do the technical challenges. Because qPCR quantification depends on amplification efficiency, multiplexing can lead to competition between targets, inconsistent sensitivity and false positives from optical crosstalk – often requiring extensive optimization to ensure reliable results.

dPCR, on the other hand, is engineered to overcome these limitations. Its partitioned, endpoint-based quantification approach is inherently suited to multiplexing. You can detect multiple targets – such as rare mutations, copy number variants or microbial markers – in a single reaction with higher accuracy. It's also ideal for RNA and miRNA expression analysis, where including a reference target in the same well is essential for normalization. New advances, like the QIAcuity High Multiplex Probe PCR Kit and QIAcuity Software Suite 3.0, support up to 8-plex reactions with enhanced crosstalk compensation – making high-order multiplexing more accessible than ever.

We offer multiplex-compatible probe-based assays and custom assay design services for both qPCR and dPCR. If you need help optimizing your multiplex setup, our technical experts can guide you through the design and detection chemistry.

Many of our qPCR assays are compatible with dPCR, but not all are fully optimized for it. If you're moving from qPCR to dPCR, it’s important to consider factors like reaction chemistry, probe compatibility and how the assay performs under dPCR’s partitioned conditions.

For example, both the QuantiNova LNA Probe PCR Assays and the miRCURY LNA miRNA Probe PCR Assays can be used in both dPCR and qPCR workflows, making them a reliable choice if you're looking to switch from relative to absolute quantification. However, because dPCR relies on endpoint detection and well partitioning, you’ll need to adjust protocols and reaction conditions.

If you’re not sure whether a specific assay is suitable for dPCR, our technical support team can help guide your decision.

Both dPCR and qPCR are powerful PCR-based methods, but they serve different purposes.

qPCR measures amplification in real time, providing relative quantification based on quantification cycles (Cq values). It is ideal for applications where comparing gene or miRNA expression levels or fold changes is sufficient.

dPCR partitions the sample into thousands of independent reactions, providing absolute quantification without requiring standard curves. It is particularly valuable when detecting low-abundance targets, rare mutations or subtle copy number variations.

If your goal is high-throughput gene or miRNA expression analysis or relative quantification, qPCR remains the standard. If you need absolute quantification, improved sensitivity for rare targets or resistance to PCR inhibitors, dPCR is the better choice.

Looking for a deeper comparison? Explore our full guide to dPCR vs. qPCR.