February 15, 2023 | PCR Solutions

dPCR and NGS: Better Together?

Often, as you start planning an experiment to tackle a burning question in your biomedical research, you encounter a number of methods that could help you find an answer. Here is a classic example. You want to detect this very interesting mutation, but how can you decide if you should use digital PCR (dPCR) or next-generation sequencing (NGS)? A good place to start is to gain a clear picture of how these two methods work.

dPCR in a snapshot

In dPCR, a PCR reaction mixture is divided into thousands of smaller reactions called partitions. The target DNAs are randomly distributed among the partitions, resulting in partitions with either zero or one or more copies. After endpoint PCR, the positive partitions containing a target emit a fluorescent signal, while the negative partitions remain dark. Based on the number of positive and negative partitions and using Poisson statistics, the exact number of target DNAs in the initial sample is determined1.

NGS in 5 strokes or less

NGS offers massively parallel analysis with high throughput from multiple samples. Most NGS methods require a library preparation step, where DNA samples (or RNA samples, converted to dsDNA) are fragmented and adapters are attached to both ends. The NGS platform uses these adapters to read the DNA fragments one nucleotide at a time, producing raw sequencing data (primary analysis). A number of bioinformatics tools exist to carry out secondary and tertiary analyses2.

dPCR and NGS: A comparison

Because they are based on different principles and due to their unique cost-benefit considerations, dPCR and NGS are often suited for particular applications. A summary of dPCR vs. NGS can be found in the table below:

  • Effective for low target numbers
  • Low limit of detection4
  • Quick results
  • High sensitivity with resolution as low as 0.0005% compared
    to qPCR (1%) and most NGS assays (2%) for known mutations6
  • Low cost/sample
  • Absolute quantification of mutant and wild-type copies
  • No prior knowledge of sequence information required
  • High sensitivity for detection of novel genes and transcripts
  • Can detect multiple genetic mutations at once
  • Comprehensive detection of known and unknown mutations
  • Single nucleotide resolution
  • Can detect only specific gene mutations
  • Requires specific assays for each gene5
  • Not useful in patients without specific markers5
  • Less cost-effective for fewer than 20 targets
  • Requires bioinformatics software 
  • Longer turnaround times
  • Lower sensitivity than dPCR6
  • Screening of known variants
  • Genotyping 
  • Serial monitoring of disease progression
  • Rapid detection of common isolated pathogens3
  • Longitudinal monitoring, such as of viral load
  • Resolution of rare mutants6
  • Studies with many targets or samples
  • Screening of patients for targeted drug therapy
  • Study of drug resistance mechanisms
  • Diagnosis where classical methods fail to identify
    causative pathogens3

Hence, your starting material, experimental design and research aims will likely determine whether you should use NGS or dPCR.

Best of both worlds: using dPCR and NGS together

Precisely because of their differences, rather than looking at dPCR and NGS as competing methods, we could consider them as complementary methods instead. Both approaches offer highly sensitive and reliable variant detection.

For example, in liquid biopsy analysis, NGS can successfully read circulating tumor-derived DNA, providing a comprehensive profiling of ctDNA as a tool for cancer biomarker discovery, such as cancer-related somatic mutations, fusion genes, and copy number variations. Once the biomarker candidates have been identified by NGS, dPCR may be well suited for further validation, and potentially used for routine testing, such as tracking resistance levels to therapies over time7. This is due to dPCR technology’s strength and cost-benefit in analysing small numbers of known markers or mutations, and that it provides absolute rather than relative quantification of circulating DNA and is not sensitive to changes in overall DNA levels.

dPCR for NGS library quantification

Optimal sequencing requires accurate quantification of functional libraries. To achieve high-yield and high-quality sequencing, NGS sequencers operate within a relatively narrow range of library loading concentration. Underloading results in low yield, low read depth, and possible failure to detect SNPs or rare sequences. Overloading leads to overclustering, thus low yield of high quality reads. Either way, underestimation or overestimation of sequencing libraries leads to suboptimal use of sequencing capacity6,8.
The most common methods for NGS library quantification are summarized in the table8 below. 

Method  Instrument  Limit of quantification
(for dsDNA 500-mer) 
of functional
Spectrophotometry-based   NanoDrop  2 ng
(3.6 billion copies) 
Mass / absolute  No standard
Not possible 
Fluorometry-based  Qubit, PicoGreen  0.3 fg – 1 ng
(550 – 1.8 billion copies/rxn) 
Mass / relative  Required:
calibrated by mass 
Not possible 
Electrophoresis-based  Bioanalyzer,
2.5 ng
(4.5 billion copies/rxn) 
Mass / relative  Required:
calibrated by mass 
Not possible 
qPCR-based  QIAquant  0.1 fg
(180 copies/rxn) 
Molecules / relative  Required:
calibrated by mass 
dPCR-based  QIAcuity  0.01 fg
(12 copies/rxn) 
Molecules / absolute  No standard

The main role of dPCR in the NGS workflow is the accurate quantification of NGS libraries without any amplification or standard bias, resulting in efficient use of NGS platforms (e.g., Illumina). Some additional benefits of using QIAcuity dPCR for NGS library quantification include:

  • Uniform loading and subsequent sequencing of pooled libraries
  • Routine testing is possible with high-throughput and rapid turnaround times
  • Coverage of all Illumina library types with one assay
  • Provide information about library quality prior to sequencing on Illumina

Although different, dPCR and NGS could be closer than two coats of paint. Each method offers unique nuances, that when used together, can strengthen your data, and help grasp the bigger picture of your research quickly and effortlessly. 

Interested in finding out more?
Watch our free webinar on using dPCR for NGS library quantification at your own convenience. 
  1. Espiñeira M, Lago F. Advances in Authenticity Testing for Fish Speciation. Advances in Food Authenticity Testing. 2016; 415-440.
  2. Heather JM, Chain B. The sequence of sequencers: The history of sequencing DNA. Genomics. 2016: 107(1):1-8.
  3. Lagunes-Castro MS, López-Monteon A, Guzmán-Gómen D, Ramos-Ligonio A. Metabarcoding and Digital PCR (dPCR): Application in the Study of Neglected Tropical Diseases. In Sperança MA. New Advances in Neglected Tropical Diseases. 2022. 
  4. Iwama E et al. Monitoring of somatic mutations in circulating cell-free DNA by digital PCR and next-generation sequencing during afatinib treatment in patients with lung adenocarcinoma positive for EGFR activating mutations. Original Articles Biotechnologies. 2017; 28(1):136-141.
  5. Panuzzo C, Jovanovski A, Shahzad AM, Cilloni D, Pergolizzi B. Revealing the Mysteries of Acute Myeloid Leukemia: From Quantitative PCR through Next-Generation Sequencing and Systemic Metabolomic Profiling. J. Clin. Med. 2022; 11(3):483.
  6. Basu AS. Digital Assays Part I: Partitioning Statistics and Digital PCR. SLAS TECHNOLOGY: Translating Life Sciences Innovation. 2017; 22(4):369-386.
  7. Coccaro N, Tota G, Anelli L, Zagaria A, Specchia G, Albano F. Digital PCR: A Reliable Tool for Analyzing and Monitoring Hematologic Malignancies. Int J Mol Sci. 2020; 21(9):3141.
  8. White III RA, Blainey P., Fan HC, Quake SR. Digital PCR provides sensitive and absolute for high throughput sequencing. BMC Genomics. 2009; 116.