qPCR remains a workhorse of genomics labs — fast, familiar, and widely available. But for all its convenience, using qPCR means making significant compromises on precision, reproducibility, and scalability. If you’re working in gene expression, copy number variation (CNV), and NGS biomarker validation workflows, you often settle for "good enough" results from qPCR because there isn’t a practical, better solution.
Countable PCR is here to finally bring researchers that solution with:
- True single-molecule isolation for precise counting, without the need for multiple technical replicates per DNA sample
- Direct counting with statistical confidence, not just data trends
- Far more insights at a lower cost per answer
- Straightforward, more affordable, and fast-to-develop workflows, even when studying multiple gene targets
The hidden costs of qPCR are lurking everywhere, like in the compromises you may be making to improve data quality. Here are some examples, and how Countable PCR eliminates them.
Running more qPCR replicates hoping to increase precision
qPCR relies on indirect measurements: amplification curves, thresholds, and standard curved. That creates variability, especially when measuring subtle expression changes or low-abundance targets.
According to a published study1, qPCR is used to detect 1.25-fold differences in gene expression — as long as you’re willing to run 18 to 40 replicates. For a 1.1-fold difference, that becomes 86 replicates!
But in many workflows — especially those involving cfDNA, rare transcripts, or low-input RNA — you don’t have the luxury of running dozens of reactions. You barely have enough material for a few replicates.
That’s not just inefficient. It’s a hard stop for precision, reproducibility, and practicality.
Countable PCR counts exactly what’s in your tube, directly. With single-molecule counting, achieve 1% CV, no matter the input. This level of precision means you’ll run fewer reactions while using less sample, and get data you trust.
Accepting subjective or biased answers from standard curves and thresholding
Accurate quantification in qPCR depends on good standards. But for many targets — rare variants, novel genes, low-expression transcripts — validated positive controls aren’t available. You’re left creating your own curves or relying on relative expression to housekeeping genes, introducing new layers of variability and bias, and increasing the number of reactions they have to set up.
Countable PCR requires no standard curves and no positive control for calibration. Quantification is direct, truly absolute, with automatic counting, and built into the system. That means you get direct counts of your targets, so you know you’re comparing targets within the same sample. Plus, no bias from standard curves or subjective thresholding.
Spending months optimizing assays, especially when studying multiple genes in parallel
While qPCR is technically capable of multiplex experiments, it rarely does at scale (Figure 1). Competition for amplification reagents causes shifts in Ct values, forcing long optimization cycles that take 6-18 months to yield results.
Figure 1: Representative qPCR amplification plot for multi-plex experimental design. As the number of targets increases, there are often severe impacts on PCR efficiency.
As a result, many labs skip this headache and stick to single-plex experiments — often using SYBR Green — to get results at the cost of doing more runs, consuming more sample and time.
Countable PCR makes multiplexing scalable, reliable, and less complex because each target is counted independently, with no competition effects. With Universal Multiplexing, the workflow is as straightforward as SYBR Green — just mix and go — with far more flexibility, sensitivity, and confidence.
Not factoring in replicates, standard curves, and repeat assays in the cost per answer
When you consider only the cost per well, qPCR appears affordable. But the cost per answer shoots up quickly when factoring in replicates, reruns, failed multiplex attempts, and time spent troubleshooting.
Though it’s quick to get started with SYBR qPCR, you’re stuck with only relative quantification and single-plex answers – not to mention, setting up a lot more reactions to probe your targets, make a standard curve, and get enough replicates for statistical confidence, especially for subtle differences.
With 1% CV, Countable PCR delivers better quality data — and results you feel confident in — in fewer reactions, without the need for standards that consume time and material.
Multiplexing with TaqMan probes in qPCR is even tougher. It takes months or even years to develop reliable multiplexing assays, and the cost of probes makes scaling prohibitive.
Figure 2: Comparison of the cost of reagents and consumables for SYBR Green singleplexing with qPCR, TaqMan multiplexing with qPCR, and Countable PCR Universal Multiplexing.
Countable PCR gives you direct, actual counts of your targets for precise quantification. Plus, consolidate your experiments and get more answers in a single reaction with straightforward multiplexing thanks to Universal Multiplexing technology, at a cost significantly lower than assays that use hydrolysis probes (Figure 2).
Countable PCR gives you precision, with none of the hidden costs and compromises of qPCR
If you're relying on qPCR and feel like you're constantly managing uncertainty, you're not alone — and it's not the biology of your sample. It's your tool.
Countable PCR delivers single-molecule quantification with the ease of standard PCR, without the hidden cost of replicates, thresholds, curves, and optimizing multiplexing. Just clean, reproducible data — from one tube, one workflow, one system.
1 - S. Weaver, et al. Taking qPCR to a higher level: Analysis of CNV reveals the power of high throughput qPCR to enhance quantitative resolution. Methods. Volume 50, Issue 4, April 2010, Pages 271-276.
