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Digital polymerase chain reaction (digital PCR, DigitalPCR, dPCR, or dePCR) is a biotechnological refinement of conventional polymerase chain reaction methods that can be used to directly quantify and clonally amplify nucleic acids strands including DNA, cDNA or RNA. The key difference between dPCR and traditional PCR lies in the method of measuring nucleic acids amounts, with the former being a more precise method than PCR, though also more prone to error in the hands of inexperienced users.^[1] A "digital" measurement quantitatively and discretely measures a certain variable, whereas an “analog” measurement extrapolates certain measurements based on measured patterns. PCR carries out one reaction per single sample. dPCR also carries out a single reaction within a sample, however the sample is separated into a large number of partitions and the reaction is carried out in each partition individually. This separation allows a more reliable collection and sensitive measurement of nucleic acid amounts. The method has been demonstrated as useful for studying variations in gene sequences — such as copy number variants and point mutations — and it is routinely used for clonal amplification of samples for next-generation sequencing.

Principles

The polymerase chain reaction method is used to quantify nucleic acids by amplifying a nucleic acid molecule with the enzyme DNA polymerase. Conventional PCR is based on the theory that amplification is exponential. Therefore, nucleic acids may be quantified by comparing the number of amplification cycles and amount of PCR end-product to those of a reference sample. However, many factors complicate this calculation, creating uncertainties and inaccuracies. These factors include the following: initial amplification cycles may not be exponential; PCR amplification eventually plateaus after an uncertain number of cycles; and low initial concentrations of target nucleic acid molecules may not amplify to detectable levels. However, the most significant limitation of PCR is that PCR amplification efficiency in a sample of interest may be different from that of reference samples. Since PCR is an exponential process, only twofold differences in amplification can be observed, greatly impacting the validity and precision of the results.

dPCR improves upon the current PCR practices by dividing up the reaction into multiple, smaller reactions. A sample is partitioned so that individual nucleic acid molecules within the sample are localized and concentrated within many separate regions. Micro well plates, capillaries, oil emulsion, and arrays of miniaturized chambers with nucleic acid binding surfaces can be used to partition the samples. A PCR solution is made similarly to a TaqMan assay, which consists of template DNA (or RNA), fluorescence-quencher probes, primers, and a PCR master mix, which contains DNA polymerase, dNTPs, MgCl₂, and reaction buffers at optimal concentrations. The PCR solution is divided into smaller reactions and are then made to run PCR individually. After multiple PCR amplification cycles, the samples are checked for fluorescence with a binary readout of “0” or “1”. The fraction of fluorescing droplets is recorded. The partitioning of the sample allows one to estimate the number of different molecules by assuming that the molecule population follows the Poisson distribution, thus accounting for the possibility of multiple target molecules inhabiting a single droplet. Using Poisson's law of small numbers, the distribution of target molecule within the sample can be accurately approximated allowing for a quantification of the target strand in the PCR product.^[2] Figure 2 shows the Poisson distribution of the copies of target molecule per droplet (CPD) based on the fraction of fluorescent droplets (p), represented by the function CPD=-ln(1-p).^[3] This model simply predicts that as the number of samples containing at least one target molecule increases, the probability of the samples containing more than one target molecule increases. In conventional PCR, the number of PCR amplification cycles is proportional to the starting copy number. Different from many peoples's belief that dPCR provides absolute quantification, digital PCR uses statistical power to provide relative quantification. For example, if Sample A, when assayed in 1 million partitions, gives one positive reaction, it does not mean that the Sample A has one starting molecule.

The benefits of dPCR include increased precision through massive sample partitioning, which ensures reliable measurements in the desired DNA sequence due to reproducibility. With basic PCR, error rates are larger when detecting small fold-change differences, however, with dPCR the error rate decreases because smaller fold-change differences can be detected in DNA sequence. The technique itself reduces the use of a larger volume of reagent needed, which inevitably will lower experiment cost. Also, dPCR is highly quantitative as it does not rely on relative fluorescence of the solution to determine the amount of amplified target DNA.

Comparison between dPCR and Real-Time PCR (qPCR)

dPCR measures the actual number of molecules (target DNA) as each molecule is in one droplet, thus making it a discrete “digital” measurement. It provides absolute quantification because dPCR measures the positive fraction of samples, which is the number of droplets that are fluorescing due to proper amplification. This positive fraction accurately indicates the initial amount of template nucleic acid. Similarly, qPCR utilizes fluorescence; however, it measures the intensity of fluorescence at specific times (generally after every amplification cycle) to determine the relative amount of target molecule (DNA), but cannot specify the exact amount without constructing a standard curve using different amounts of a defined standard. It gives the threshold per cycle (CT) and the difference in CT is used to calculate the amount of initial nucleic acid. As such, qPCR is an analog measurement, which may not be as precise due to the extrapolation required to attain a measurement.^[4] It should be noted that the previous reference was authored by employees of Bio-Rad, which provides commercial kits and reagents for dPCR, and therefore stands to profit from their promotion and sale.

dPCR measures the amount of DNA after amplification is complete and then determines the fraction of replicates. This is representative of an endpoint measurement as it requires the observation of the data after the experiment is completed. In contrast, qPCR records the relative fluorescence of the DNA at specific points during the amplification process, which requires stops in the experimental process. This “real-time” aspect of qPCR may theoretically affect results due to the stopping of the experiment.^{[citation needed]} In practice, however, most qPCR thermal cyclers read each sample's fluorescence very quickly at the end of the annealing/extension step before proceeding to the next melting step, meaning this hypothetical concern is not actually relevant or applicable for the vast majority of researchers.

qPCR is unable to distinguish differences in gene expression or copy number variations that are smaller than twofold.^[5] It is difficult to identify alleles with frequencies of less than 1% because highly abundant, common alleles would be matched with similar sequences.^{[clarification needed]} On the other hand, dPCR has been shown to detect a differences of less than 30% in gene expression, distinguish between copy number variations of that differ by only 1 copy, and identify alleles that occur at frequencies less than 0.1%.^[6]

Applications

Digital PCR has many applications in basic research, clinical diagnostics and environmental testing. Its uses include pathogen detection and digestive health analysis;^[7]^[8] liquid biopsy for cancer monitoring, organ transplant rejection monitoring and non-invasive prenatal testing for serious genetic abnormalities;^[9]^[10]^[11]^[12]^[13]^[14]^[15]^[16] copy number variation analysis,^[17]^[18]^[19] rare sequence detection,^[16]^[20]^[21]^[22] gene expression profiling and single-cell analysis;^[23]^[24]^[21]^[25]^[26]^[27]^[28] the detection of DNA contaminants in bioprocessing,^[29] the validation of gene edits and detection of specific methylation changes in DNA as biomarkers of cancer.^[30]^[31]^[32]^[33] dPCR is also frequently used as an orthogonal method to confirm rare mutations detected through next-generation sequencing (NGS) and to validate NGS libraries.^[34]^[35]^[36]

Absolute quantification

dPCR enables the absolute and reproducible quantification of target nucleic acids at single-molecule resolution.^[21]^[37]^[22]^[38]^[39]^[40] Unlike analogue quantitative PCR (qPCR), however, absolute quantification with dPCR does not require a standard curve).^[37] dPCR also has a greater tolerance for inhibitor substances and PCR assays that amplify inefficiently as compared to qPCR.^[41]^[42]

dPCR can quantify, for example, the presence of specific sequences from contaminating genetically modified organisms in foodstuffs,^[43] viral load in the blood,^[44] biomarkers of neurodegenerative disease in cerebral spinal fluid,^[45] and fecal contamination in drinking water. ^[46]

Copy number variation

An alteration in copy number state with respect to a single-copy reference locus is referred to as a “copy number variation” (CNV) if it appears in germline cells, or a copy number alteration (CNA) if it appears in somatic cells.^[47] A CNV or CNA could be due to a deletion or amplification of a locus with respect to the number of copies of the reference locus present in the cell, and together, they are major contributors to variability in the human genome.^[48]^[49]^[50] They have been associated with cancers;^[51]^[52]^[53] neurological,^[54] psychiatric,^[55]^[56] and autoimmune diseases;^[57] and adverse drug reactions.^[58] However, it is difficult to measure these allelic variations with high precision using other methods such as qPCR, thus making phenotypic and disease associations with altered CNV status challenging.^[59]^[60]

The large number of “digitized,” endpoint measurements made possible by sample partitioning enables dPCR to resolve small differences in copy number with better accuracy and precision when compared to other methods such as SNP-based microarrays^[22]^[61] or qPCR.^[62]^[22]^[63]^[64] qPCR is limited in its ability to precisely quantify gene amplifications in several diseases, including Crohn’s disease, HIV-1 infection, and obesity.^[65]^[60]^[64]

dPCR was designed to measure the concentration of a nucleic acid target in copies per unit volume of the sample. When operating in dilute reactions where less than ~10% of the partitions contain a desired target (referred to as “limiting dilution”), copy number can be estimated by comparing the number of fluorescent droplets arising from a target CNV with the number of fluorescent droplets arising from an invariant single-copy reference locus.^[17] In fact, both at these lower target concentrations and at higher ones where multiple copies of the same target can co-localize to a single partition, Poisson statistics are used to correct for these multiple occupancies to give a more accurate value for each target’s concentration.^[66]^[67]

Digital PCR has been used to uncover both germline and somatic variation in gene copy number between humans^[68] and to study the link between amplification of HER2 (ERBB2) and breast cancer progression.^[69]^[70]^[71]^[19]

Rare mutation and rare allele detection

Partitioning in digital PCR increases sensitivity and allows for detection of rare events, especially single nucleotide variants (SNVs), by isolating or greatly diminishing the target biomarker signal from potentially competing background.^[22] These events can be organized into two classes: rare mutation detection and rare sequence detection.

Rare Mutation Detection

Rare mutation detection occurs when a biomarker exists within a background of a highly abundant counterpart that differs by only a single nucleotide variant (SNV). Digital PCR has been shown to be capable of detecting mutant DNA in the presence of a 100,000-fold excess of wild type background, which is 1,000 times more sensitive than achievable with conventional qPCR.^[22]

Rare Sequence Detection

Digital PCR can detect rare sequences such as HIV DNA in patients with HIV,^[16] and DNA from fecal bacteria in ocean and other water samples for assessing water quality.^[72] dPCR can detect sequences as rare as 1 in every 1,250,000 cells.^[16]

Liquid Biopsy

dPCR’s ability to detect rare mutations may be of particular benefit in the clinic through the use of the liquid biopsy, a generally noninvasive strategy for detecting and monitoring disease via bodily fluids.^[9]^[73] Researchers have used liquid biopsy to monitor tumor load, treatment response and disease progression in cancer patients by measuring rare mutations in circulating tumor DNA (ctDNA) in a variety of biological fluids from patients including blood, urine and cerebrospinal fluid.^[9]^[74]^[75]. Early detection of ctDNA (as in molecular relapse) may lead to earlier administration of an immunotherapy or a targeted therapy specific for the patient’s mutation signature, potentially improving chances of the treatment’s effectiveness rather than waiting for clinical relapse before altering treatment. Liquid biopsies can have turnaround times of a few days, compared to two to four weeks or longer for tissue-based tests.^[76]^[77] This reduced time to results has been used by physicians to expedite treatments tailored to biopsy data.^[76]

In 2016, a prospective trial using dPCR at the Dana-Farber Cancer Institute authenticated the clinical benefit of liquid biopsy as a predictive diagnostic tool for patients with non-small-cell lung cancer.^[78] The application of liquid biopsy tests have also been studied in patients with breast,^[79] colorectal,^[80]^[81] gynecologic,^[82] and bladder cancers^[74]^[83] to monitor both the disease load and the tumor’s response to treatment.

Gene expression and RNA quantification

Gene expression and RNA quantification studies have benefited from the increased precision and absolute quantification of dPCR. RNA quantification can be accomplished via RT-PCR, wherein RNA is reverse-transcribed into cDNA in the partitioned reaction itself, and the number of RNA molecules originating from each transcript (or allelic transcript) is quantified via dPCR (ref).^[23]

One can often achieve greater sensitivity and precision by using dPCR rather than qPCR to quantify RNA molecules in part because it does not require use of a standard curve for quantification.^[84] dPCR is also more resilient to PCR inhibitors for the quantification of RNA than qPCR.^[41]^[8]

dPCR can detect and quantify more individual target species per detection channel than qPCR by virtue of being able to distinguish targets based on their differential fluorescence amplitude or by the use of distinctive color combinations for their detection.^[85] As an example of this, a 2-channel dPCR system has been used to detect in a single well the expression of four different splice variants of human telomerase reverse transcriptase, a protein that is more active in most tumor cells than in healthy cells.^[86]

Alternative Uses for Partitioning

Using the dynamic partitioning capabilities employed in dPCR, improved NGS sequencing can be achieved by partitioning of complex PCR reactions prior to amplification to give more uniform amplification across many distinct amplicons for [massive parallel sequencing|NGS]] analysis.^[87]^[88] Additionally, the improved specificity of complex PCR amplification reactions in droplets has been shown to greatly reduce the number of iterations required to select for high affinity aptamers in the SELEX method.^[89] Partitioning can also allow for more robust measurements of telomerase activity from cell lysates.^[90]^[91]

Droplet Digital PCR

In Droplet Digital PCR (ddPCR), a 20 microliter sample reaction including assay primers and either Taqman probes or an intercalating dye, is divided into ~20,000 nanoliter-sized oil droplets through a water-oil emulsion technique, thermocycled to endpoint in a 96-well PCR plate, and fluorescence amplitude read for all droplets in each sample well in a droplet flow cytometer.^[22]^[63]^[92]

History

dPCR rose out of an approach first published in 1988 by Cetus Corporation when researchers showed single β-globin molecules could be detected and amplified by PCR.^[93]^[94] This was achieved by dividing the sample so some reactions contained the molecule and others did not. In 1990, Peter Simmonds and AJ Brown used this concept to quantify a molecule for the first time.^[95] Alex Morley and Pamela Sykes formally established the method as a quantitative technique in 1992.^[39]

In 1999, Bert Vogelstein and Kenneth Kinzler coined the term “digital PCR” and showed that the technique could be used to find rare cancer mutations.^[96] However, dPCR was difficult to perform; it was labor intensive, required a lot of training to do properly, and was difficult to do in large quantities. ^[96]

In 2003, Kinzler and Vogelstein continued to refine dPCR and created an improved method that they called BEAMing technology, an acronym for “beads, emulsion, amplification and magnetics.” The new protocol used emulsion to compartmentalize amplification reactions in a single tube. This change made it possible for scientists to scale the method to thousands of reactions in a single run.^[97]^[98]^[99]

In 2006, Fluidigm introduced the first commercial system for dPCR based on integrated fluidic circuits (chips) that partition samples using nano-chambers.^[100]^[101]

Companies developing commercial dPCR systems have integrated technologies like automated partitioning of samples, digital counting of nucleic acid targets, and increasing droplet count that can help the process be more efficient.^[100]^[101]^[102]^[103]

RainDance Technologies (now part of Bio-Rad Laboratories) created a PCR system that can divide samples into 10 million picoliter-sized droplets in 2013.^[102]^[104] The first instrument to detect three colors per sample came on the market in 2016 from Stilla Technologies.^[105]

In recent years, scientists have developed and commercialized dPCR-based diagnostics for several conditions, including non-small cell lung cancer and Down’s Syndrome.^[106]^[107] The first dPCR system for clinical use was CE-marked in 2017 and cleared by the US Food and Drug Administration in 2019, for diagnosing chronic myeloid leukemia.^[108]

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@@ Line 12: / Line 12: @@
 The benefits of dPCR include increased precision through massive sample partitioning, which ensures reliable measurements in the desired DNA sequence due to reproducibility. With basic PCR, error rates are larger when detecting small fold-change differences, however, with dPCR the error rate decreases because smaller fold-change differences can be detected in DNA sequence. The technique itself reduces the use of a larger volume of reagent needed, which inevitably will lower experiment cost. Also, dPCR is highly quantitative as it does not rely on relative fluorescence of the solution to determine the amount of amplified target DNA.
-===Droplet Digital PCR===
-[[File:Oil Emulsion Technique.png|thumb|Figure 3. Representation of oil emulsion technique used in digital droplet PCR]]
-In Digital Droplet PCR (ddPCR) the PCR solution is divided into smaller reactions through a water-in-oil emulsion technique, which are then made to run PCR individually. As shown in Figure 3, the PCR sample is partitioned into nanoliter-size samples and encapsulated into water droplets, which are surrounded by the oil phase.<ref>{{cite web |url=http://www.bio-rad.com/en-us/applications-technologies/droplet-digital-pcr-ddpcr-technology |title= Droplet Digital™ PCR (ddPCR™) Technology|publisher=[[Bio-Rad]] |access-date=2018-05-26}}</ref> The water droplets are made using a droplet generator that applies a vacuum to each of the wells.<ref name="Pinheiro2012">{{cite journal | vauthors = Pinheiro LB, Coleman VA, Hindson CM, Herrmann J, Hindson BJ, Bhat S, Emslie KR | title = Evaluation of a droplet digital polymerase chain reaction format for DNA copy number quantification | journal = Analytical Chemistry | volume = 84 | issue = 2 | pages = 1003–11 | date = January 2012 | pmid = 22122760 | pmc = 3260738 | doi = 10.1021/ac202578x | doi-access = free }}</ref> Approximately 20,000 oil droplets are made from each 20 μL sample.
 == Comparison between dPCR and Real-Time PCR (qPCR) ==
@@ Line 26: / Line 22: @@
 ==Applications==
 {{Advert|section|date=February 2017}}
 Digital PCR has many applications in [[basic research]], [[Medical laboratory|clinical diagnostics]] and environmental testing. Its uses include [[pathogen]] detection and [[digestive health]] analysis;<ref name="WitteFister2016">{{cite journal|last1=Witte|first1=Anna Kristina|display-authors=et al|title=Evaluation of the performance of quantitative detection of the Listeria monocytogenes prfA locus with droplet digital PCR|journal=Analytical and Bioanalytical Chemistry|volume=408|issue=27|year=2016|pages=7583–7593|issn=1618-2642|doi=10.1007/s00216-016-9861-9}}</ref><ref name="StauberShaikh2016">{{cite journal|last1=Stauber|first1=Jennifer|display-authors=et al|title=Droplet digital PCR quantifies host inflammatory transcripts in feces reliably and reproducibly|journal=Cellular Immunology|volume=303|year=2016|pages=43–49|issn=00088749|doi=10.1016/j.cellimm.2016.03.007|pmid=27063479}}</ref> [[liquid biopsy]] for [[cancer]] monitoring, organ [[transplant rejection]] monitoring and non-invasive [[prenatal testing]] for serious [[mutation|genetic abnormalities]];<ref name="Skibo">{{cite news |last=Skibo |first=Scott |date=23 Feb 2018 |title= Has Tumor Profiling Caught Up to Cancer?|url=https://thepathologist.com/diagnostics/has-tumor-profiling-caught-up-to-cancer |access-date=23 July 2019}}</ref><ref name="Hirsch">{{cite news |last=Hirsch |first=Fred |date=27 July 2018 |title= Guidelines highlight 'best practices' for liquid biopsy during treatment of non-small cell lung cancer|url=https://www.healio.com/hematology-oncology/lung-cancer/news/in-the-journals/%7B7a38fda7-6a5d-4e0b-a78b-60f6a64d6bdc%7D/guidelines-highlight-best-practices-for-liquid-biopsy-during-treatment-of-non-small-cell-lung-cancer |access-date=23 July 2019}}</ref><ref name="GWdPCRtech">{{cite news |last=Johnson |first=Madeleine |date=12 Jan 2018 |title= Bio-Rad Continues to Advance Digital PCR Tech, Liquid Biopsy Tests Into Commercial Clinical Market|url=https://www.genomeweb.com/molecular-diagnostics/bio-rad-continues-advance-digital-pcr-tech-liquid-biopsy-tests-commercial#.XTcmipNKh-V |access-date=23 July 2019}}</ref><ref name="OxnardPaweletz2014">{{cite journal|last1=Oxnard|first1=G. R.|display-authors=et al |title=Noninvasive Detection of Response and Resistance in EGFR-Mutant Lung Cancer Using Quantitative Next-Generation Genotyping of Cell-Free Plasma DNA|journal=Clinical Cancer Research|volume=20|issue=6|year=2014|pages=1698–1705|issn=1078-0432|doi=10.1158/1078-0432.CCR-13-2482|pmid=24429876}}</ref><ref name="Schütz2017">{{cite journal|last1=Schütz|first1=E.|display-authors=et al |title=Graft-derived cell-free DNA, a noninvasive early rejection and graft damage marker in liver transplantation: A prospective, observational, multicenter cohort study|journal=PLoS Medicine|volume=14|issue=4|pages=e1002286|year=2017|doi=10.1371/journal.pmed.1002286|pmid=28441386}}</ref><ref name="Lee2015">{{cite journal|last1=Lee|first1=S.Y.|last2=Hwang|first2=S.Y. |title=Application of digital polymerase chain reaction technology for noninvasive prenatal test|journal=Journal of Genetic Medicine |volume=12|issue=2|pages=72–78|year=2015 |doi=10.5734/JGM.2015.12.2.72 |issn=2383-8442}}</ref><ref name="Gu2014">{{cite journal|last1=Gu|first1=W.|display-authors=et al |title=Noninvasive prenatal diagnosis in a fetus at risk for methylmalonic acidemia|journal=Journal of Genetic Medicine |volume=16|issue=7|pages=564–567|year=2014|doi=10.1038/gim.2013.194|pmid=24406457|pmc=4079742}}</ref><ref name="Strain2013">{{cite journal|last1=Strain|first1=M.|display-authors=et al |title=Highly Precise Measurement of HIV DNA by Droplet Digital PCR|journal=PLOS ONE |volume=8|issue=4|pages=e55943|year=2013|doi= 10.1371/journal.pone.0055943|pmid=23573183|bibcode=2013PLoSO...855943S}}</ref> [[copy number variation]] analysis,<ref name="Bell2018">{{cite book|last1=Bell|first1=Avery Davis|title=Digital PCR|last2=Usher|first2=Christina L.|last3=McCarroll|first3=Steven A.|chapter=Analyzing Copy Number Variation with Droplet Digital PCR|volume=1768|year=2018|pages=143–160|issn=1064-3745|doi=10.1007/978-1-4939-7778-9_9|pmid=29717442|series=Methods in Molecular Biology|isbn=978-1-4939-7776-5}}</ref><ref name="ShodaIchikawa2016">{{cite journal |last1=Shoda|first1=Katsutoshi|display-authors=et al|title=Monitoring the HER2 copy number status in circulating tumor DNA by droplet digital PCR in patients with gastric cancer|journal=Gastric Cancer|volume=20|issue=1|year=2016|pages=126–135|issn=1436-3291|doi=10.1007/s10120-016-0599-z|pmid=26874951}}</ref><ref name="Gevensleben2013">{{cite journal|last1=Gevensleben|first1=H.|display-authors=et al|title=Noninvasive Detection of HER2 Amplification with Plasma DNA Digital PCR|journal=Clinical Cancer Research|volume=19|issue=12|year=2013|pages=3276–3284|issn=1078-0432|doi=10.1158/1078-0432.CCR-12-3768|pmid=23637122}}</ref> rare sequence detection,<ref name="Strain2013" /><ref name="UchiyamaNakashima2016">{{cite journal|last1=Uchiyama|first1=Yuri|display-authors=et al|title=Ultra–sensitive droplet digital PCR for detecting a low–prevalence somatic GNAQ mutation in Sturge–Weber syndrome|journal=Scientific Reports|volume=6|issue=1|year=2016|issn=2045-2322|doi=10.1038/srep22985|pmid=26957145}}</ref><ref name="Marusina">{{cite news |last=Marusina |first=Kate |date=1 Oct 2017 |title= Positioning Digital PCR for Sharper Genomic Views |url=https://www.genengnews.com/magazine/positioning-digital-pcr-for-sharper-genomic-views/ |access-date=23 July 2019}}</ref><ref name="HindsonNess2011">{{cite journal|last1=Hindson|first1=Benjamin J.|display-authors=et al|title=High-Throughput Droplet Digital PCR System for Absolute Quantitation of DNA Copy Number|journal=Analytical Chemistry|volume=83|issue=22|year=2011|pages=8604–8610|issn=0003-2700|doi=10.1021/ac202028g|pmid=22035192}}</ref> [[gene expression profiling]] and [[single-cell analysis]];<ref name="Kamitaki2018">{{cite book|last1=Kamitaki|first1=Nolan|title=Digital PCR|display-authors=et al|chapter=Using Droplet Digital PCR to Analyze Allele-Specific RNA Expression|volume=1768|year=2018|pages=401–422|issn=1064-3745|doi=10.1007/978-1-4939-7778-9_23|pmid=29717456|series=Methods in Molecular Biology|isbn=978-1-4939-7776-5}}</ref><ref name="MillierStamp2017">{{cite journal|last1=Millier|first1=Melanie J.|display-authors=et al|title=Digital-PCR for gene expression: impact from inherent tissue RNA degradation|journal=Scientific Reports|volume=7|issue=1|pages=17235|year=2017|issn=2045-2322|doi=10.1038/s41598-017-17619-0|pmid=29222437|bibcode=2017NatSR...717235M}}</ref><ref name="Marusina" /><ref name="GENHepB">{{cite news |date=12 Apr 2018 |title= Highly Sensitive Detection of Hepatitis B Using ddPCR |url=https://www.genengnews.com/topics/omics/highly-sensitive-detection-of-hepatitis-b-using-ddpcr/ |access-date=23 July 2019}}</ref><ref name="Jang2017">{{cite journal|last1=Jang|first1=Minjeong|display-authors=et al|title=Droplet-based digital PCR system for detection of single-cell level of foodborne pathogens|journal=BioChip Journal|volume=11|issue=4|pages=329–337|year=2017|issn=2092-7843|doi=10.1007/s13206-017-1410-x}}</ref><ref name="Igarashi2017">{{cite journal|last1=Igarashi|first1=Yuka|display-authors=et al|title=Single Cell-Based Vector Tracing in Patients with ADA-SCID Treated with Stem Cell Gene Therapy|journal=Molecular Therapy - Methods & Clinical Development|volume=6|year=2017|pages=8–16|issn=23290501|doi=10.1016/j.omtm.2017.05.005|pmid=28626778}}</ref><ref name="Albayrak2016">{{cite journal|last1=Albayrak|first1=Cem|display-authors=et al|title=Digital Quantification of Proteins and mRNA in Single Mammalian Cells|journal=Molecular Cell|volume=61|issue=6|year=2016|pages=914–24|issn=10972765|doi=10.1016/j.molcel.2016.02.030|pmid=26990994}}</ref> the detection of [[DNA]] contaminants in bioprocessing,<ref name="Hussain2016">{{cite journal|last1=Hussain|first1=Musaddeq|display-authors=et al|title=A direct droplet digital PCR method for quantification of residual DNA in protein drugs produced in yeast cells|journal=Journal of Pharmaceutical and Biomedical Analysis|volume=123|year=2016|pages=128–131|issn=07317085|doi=10.1016/j.jpba.2016.01.050|pmid=26896631}}</ref> the validation of [[genetic engineering|gene edits]] and detection of specific [[DNA methylation|methylation changes in DNA]] as [[Cancer biomarker|biomarkers of cancer]].<ref name="Miyaoka2014">{{cite journal|last1=Miyaoka|first1=Yuichiro|display-authors=et al|title=Isolation of single-base genome-edited human iPS cells without antibiotic selection |journal=Nature Methods|volume=11|issue=3|year=2014|pages=291–293|doi=10.1038/nmeth.2840|pmid=24509632|pmc=4063274}}</ref><ref name="Mock2016">{{cite journal|last1=Mock|first1=Ulrike|display-authors=et al|title=Digital PCR to assess gene-editing frequencies (GEF-dPCR) mediated by designer nucleases |journal=Nature Protocols|volume=11|year=2016|pages=598–615|doi=10.1038/nmeth.2840|pmid=24509632|pmc=4063274}}</ref><ref name="Nelson2015">{{cite journal|last1=Nelson|first1=C. E.|display-authors=et al|title=In vivo genome editing improves muscle function in a mouse model of Duchenne muscular dystrophy |journal=Science |volume=351|issue=6271 |year=2015|pages=403–407|issn=0036-8075|doi=10.1126/science.aad5143|pmid=26721684}}</ref><ref name="Miyaoka2016">{{cite journal|last1=Miyaoka|first1=Yuichiro|display-authors=et al|title=Systematic quantification of HDR and NHEJ reveals effects of locus, nuclease, and cell type on genome-editing |journal=Scientific Reports |volume=61 |pages=23549|year=2016|doi=10.1038/srep23549|pmid=27030102|bibcode=2016NatSR...623549M}}</ref> dPCR is also frequently used as an orthogonal method to confirm rare mutations detected through [[Massive parallel sequencing|next-generation sequencing]] (NGS) and to validate NGS [[Genomic library|libraries]].<ref name="GutteryPage2015">{{cite journal|last1=Guttery|first1=D. S.|display-authors=et al|title=Noninvasive Detection of Activating Estrogen Receptor 1 (ESR1) Mutations in Estrogen Receptor-Positive Metastatic Breast Cancer|journal=Clinical Chemistry|volume=61|issue=7|year=2015|pages=974–982|issn=0009-9147|doi=10.1373/clinchem.2015.238717|pmid=25979954}}</ref><ref name="RobinLudlow2016">{{cite journal|last1=Robin|first1=Jérôme D.|display-authors=et al|title=Comparison of DNA Quantification Methods for Next Generation Sequencing|journal=Scientific Reports|volume=6|issue=1|pages=24067|year=2016|issn=2045-2322|doi=10.1038/srep24067|pmid=27048884|bibcode=2016NatSR...624067R}}</ref><ref name="Aigrain2016">{{cite journal|last1=Aigrain|first1=Louise|display-authors=et al|title=Quantitation of next generation sequencing library preparation protocol efficiencies using droplet digital PCR assays - a systematic comparison of DNA library preparation kits for Illumina sequencing|journal=BMC Genomics|volume=17|issue=1|pages=458|year=2016|issn=1471-2164|doi=10.1186/s12864-016-2757-4|pmid=27297323|pmc=4906846}}</ref>
+=== Absolute quantification ===
+dPCR enables the absolute and reproducible quantification of target nucleic acids at single-molecule resolution.<ref name="Marusina" /><ref name="BrunettoMassoud2014">{{cite journal|last1=Brunetto|first1=Giovanna S.|display-authors=et al|title=Digital droplet PCR (ddPCR) for the precise quantification of human T-lymphotropic virus 1 proviral loads in peripheral blood and cerebrospinal fluid of HAM/TSP patients and identification of viral mutations|journal=Journal of NeuroVirology|volume=20|issue=4|year=2014|pages=341–351|issn=1355-0284|doi=10.1007/s13365-014-0249-3}}</ref><ref name="HindsonNess2011" /><ref name="PinheiroColeman2011">{{cite journal|last1=Pinheiro|first1=Leonardo B.|display-authors=et al|title=Evaluation of a Droplet Digital Polymerase Chain Reaction Format for DNA Copy Number Quantification|journal=Analytical Chemistry|volume=84|issue=2|year=2011|pages=1003–1011|issn=0003-2700|doi=10.1021/ac202578x}}</ref><ref name="skykes1992" /><ref name="VogelsteinKinzler1999">{{cite journal|last1=Vogelstein|first1=B.|last2=Kinzler|first2=K. W.|title=Digital PCR|journal=Proceedings of the National Academy of Sciences|volume=96|issue=16|year=1999|pages=9236–9241|issn=0027-8424|doi=10.1073/pnas.96.16.9236}}</ref> Unlike analogue [[Real-time polymerase chain reaction|quantitative PCR]] (qPCR), however, absolute quantification with dPCR does not require a [[standard curve]]).<ref name="BrunettoMassoud2014" /> dPCR also has a greater tolerance for inhibitor substances and PCR assays that amplify inefficiently as compared to qPCR.<ref name="RačkiDreo2014">{{cite journal|last1=Rački|first1=Nejc|display-authors=et al|title=Reverse transcriptase droplet digital PCR shows high resilience to PCR inhibitors from plant, soil and water samples|journal=Plant Methods|volume=10|issue=1|year=2014|issn=1746-4811|doi=10.1186/s13007-014-0042-6}}</ref><ref name="DingleSedlak2013">{{cite journal|last1=Dingle|first1=T. C.|display-authors=et al|title=Tolerance of Droplet-Digital PCR vs Real-Time Quantitative PCR to Inhibitory Substances|journal=Clinical Chemistry|volume=59|issue=11|year=2013|pages=1670–1672|issn=0009-9147|doi=10.1373/clinchem.2013.211045}}</ref>
+dPCR can quantify, for example, the presence of specific sequences from contaminating [[genetically modified organisms]] in foodstuffs,<ref name="DobnikSpilsberg2018">{{cite journal|last1=Dobnik|first1=David|display-authors=et al|title=Multiplex Droplet Digital PCR Protocols for Quantification of GM Maize Events|journal=Methods of Molecular Biology|volume=1768|year=2018|pages=69–98|issn=1064-3745|doi=10.1007/978-1-4939-7778-9_5}}</ref> viral load in the blood,<ref name="VellucciLeibovitch2018">{{cite journal|last1=Vellucci|first1=Ashley|display-authors=et al|title=Using Droplet Digital PCR to Detect Coinfection of Human Herpesviruses 6A and 6B (HHV-6A and HHV-6B) in Clinical Samples|journal=Methods in Molecular Biology|volume=1768|year=2018|pages=99–109|issn=1064-3745|doi=10.1007/978-1-4939-7778-9_6}}</ref> biomarkers of neurodegenerative disease in cerebral spinal fluid,<ref name="PodlesniyTrullas2018">{{cite journal|last1=Podlesniy|first1=Petar|display-authors=et al|title=Biomarkers in Cerebrospinal Fluid: Analysis of Cell-Free Circulating Mitochondrial DNA by Digital PCR|journal=Methods in Molecular Biology|volume=1768|year=2018|pages=111–126|issn=1064-3745|doi=10.1007/978-1-4939-7778-9_7}}</ref> and fecal contamination in drinking water. <ref name="Cao2018">{{cite journal|last1=Cao|first1=Yiping|display-authors=et al|title=Testing of General and Human-Associated Fecal Contamination in Waters|journal=Methods in Molecular Biology|volume=1768|year=2018|pages=127-140|issn=1064-3745|doi=10.1007/978-1-4939-7778-9_8}}</ref>
+=== Copy number variation ===
+An alteration in copy number state with respect to a single-copy reference locus is referred to as a “[[copy-number variation|copy number variation]]” (CNV) if it appears in germline cells, or a copy number alteration (CNA) if it appears in somatic cells.<ref name="LiLee2009">{{cite journal|last1=Li|first1=Wentian|display-authors=et al|title=Copy-number-variation and copy-number-alteration region detection by cumulative plots|journal=BMC Bioinformatics|volume=10|issue=S1|year=2009|issn=1471-2105|doi=10.1186/1471-2105-10-S1-S67}}</ref> A CNV or CNA could be due to a deletion or amplification of a locus with respect to the number of copies of the reference locus present in the cell, and together, they are major contributors to variability in the [[human genome]].<ref name="KorenHandsaker2014">{{cite journal |last1=Koren|first1=Amnon|display-authors=et al|title=Genetic Variation in Human DNA Replication Timing|journal=Cell|volume=159|issue=5|year=2014|pages=1015–1026|issn=00928674|doi=10.1016/j.cell.2014.10.025}}</ref><ref name="ScienceWebinar">{{cite news |last=Sanders |first=Sean |date=16 Jul 2008 |title= CNVs vs SNPs: Understanding Human Structural Variation in Disease|url=https://www.sciencemag.org/custom-publishing/webinars/cnvs-vs-snps-understanding-human-structural-variation-disease |access-date=24 July 2019}}</ref><ref name="MarshallHowrigan2016">{{cite journal|last1=Marshall|first1=Christian R|display-authors=et al|title=Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects|journal=Nature Genetics|volume=49|issue=1|year=2016|pages=27–35|issn=1061-4036|doi=10.1038/ng.3725}}</ref> They have been associated with cancers;<ref name="ShlienMalkin2009">{{cite journal|last1=Shlien|first1=Adam|last2=Malkin|first2=David|title=Copy number variations and cancer|journal=Genome Medicine|volume=1|issue=6|year=2009|pages=62|issn=1756-994X|doi=10.1186/gm62}}</ref><ref name="LauerGresham2019">{{cite journal|last1=Lauer|first1=Stephanie|last2=Gresham|first2=David|title=An evolving view of copy number variants|journal=Current Genetics|year=2019|issn=0172-8083|doi=10.1007/s00294-019-00980-0}}</ref><ref name="CNVGEN">{{cite news |date=5 Sep 2018 |title= Copy Number Alteration Found to Be Associated with Cancer Mortality |url=https://www.genengnews.com/news/copy-number-alteration-found-to-be-associated-with-cancer-mortality/|access-date=24 July 2019}}</ref> neurological,<ref name="GuLupski2008">{{cite journal|last1=Gu|first1=W.|last2=Lupski|first2=J.R.|title=CNV and nervous system diseases – what’s new?|journal=Cytogenetic and Genome Research|volume=123|issue=1-4|year=2008|pages=54–64|issn=1424-8581|doi=10.1159/000184692}}</ref> psychiatric,<ref name="ThaparCooper2013">{{cite journal|last1=Thapar|first1=Anita|last2=Cooper|first2=Miriam|title=Copy Number Variation: What Is It and What Has It Told Us About Child Psychiatric Disorders?|journal=Journal of the American Academy of Child & Adolescent Psychiatry|volume=52|issue=8|year=2013|pages=772–774|issn=08908567|doi=10.1016/j.jaac.2013.05.013}}</ref><ref name="Sekar2016">{{cite journal|last1=Sekar|first1=Aswin|display-authors=et al|title=Schizophrenia risk from complex variation of complement component 4|journal=Nature|volume=530|year=2016|pages=177-183|issn=08908567|doi=10.1038/nature16549}}</ref> and autoimmune diseases;<ref name="YimJung2015">{{cite journal|last1=Yim|first1=Seon-Hee|display-authors=et al|title=Clinical implications of copy number variations in autoimmune disorders|journal=The Korean Journal of Internal Medicine|volume=30|issue=3|year=2015|pages=294|issn=1226-3303|doi=10.3904/kjim.2015.30.3.294}}</ref> and adverse drug reactions.<ref name="HeHoskins2011">{{cite journal|last1=He|first1=Yijing|last2=Hoskins|first2=Janelle M.|last3=McLeod|first3=Howard L.|title=Copy number variants in pharmacogenetic genes|journal=Trends in Molecular Medicine|volume=17|issue=5|year=2011|pages=244–251|issn=14714914|doi=10.1016/j.molmed.2011.01.007}}</ref> However, it is difficult to measure these allelic variations with high precision using other methods such as qPCR, thus making phenotypic and disease associations with altered CNV status challenging.<ref name="Gonzalez2005">{{cite journal|last1=Gonzalez|first1=E.|title=The Influence of CCL3L1 Gene-Containing Segmental Duplications on HIV-1/AIDS Susceptibility|journal=Science|volume=307|issue=5714|year=2005|pages=1434–1440|issn=0036-8075|doi=10.1126/science.1101160}}</ref><ref name="UnutmazLiu2010">{{cite journal|last1=Unutmaz|first1=Derya|display-authors=et al|title=CCL3L1 Copy Number Variation and Susceptibility to HIV-1 Infection: A Meta-Analysis|journal=PLoS ONE|volume=5|issue=12|year=2010|pages=e15778|issn=1932-6203|doi=10.1371/journal.pone.0015778}}</ref>
+The large number of “digitized,” endpoint measurements made possible by sample partitioning enables dPCR to resolve small differences in copy number with better [[accuracy and precision]] when compared to other methods such as SNP-based microarrays<ref name="HindsonNess2011" /><ref name="Dube2008">{{cite journal|last1=Dube|first1=Simant|last2=Qin|first2=Jian |last3=Ramakrishnan|first3=Ramesh|title=Mathematical Analysis of Copy Number Variation in a DNA Sample Using Digital PCR on a Nanofluidic Device|journal=PLoS ONE|volume=3|issue=8|year=2008|pages=e2876|issn=1932-6203|doi=10.1371/journal.pone.0002876}}</ref> or qPCR.<ref name="HughesmanLu2017">{{cite journal|last1=Hughesman|first1=Curtis B.|display-authors=et al|title=Detection of clinically relevant copy number alterations in oral cancer progression using multiplexed droplet digital PCR|journal=Scientific Reports|volume=7|issue=1|year=2017|issn=2045-2322|doi=10.1038/s41598-017-11201-4}}</ref><ref name="HindsonNess2011" /><ref name="Pinheiro2012" /><ref name="Usher2015">{{cite journal|last1=Usher|first1=Christina|display-authors=et al|title=Structural forms of the human amylase locus and their relationships to SNPs, haplotypes and obesity|journal=Nature Genetics|volume=47|year=2015|pages=921-925|doi=10.1038/ng.3340}}</ref> qPCR is limited in its ability to precisely quantify gene amplifications in several diseases, including Crohn’s disease, HIV-1 infection, and obesity.<ref name="Aldhous2010">{{cite journal|last1=Aldhous|first1=Marian C.|display-authors=et al|title=Measurement methods and accuracy in copy number variation: failure to replicate associations of beta-defensin copy number with Crohn's disease|journal=Human Molecular Genetics|volume=19|issue=24|year=2010|pages=4930–4938|issn=1460-2083|doi=10.1093/hmg/ddq411}}</ref><ref name="UnutmazLiu2010">{{cite journal|last1=Unutmaz|first1=Derya|display-authors=et al|title=CCL3L1 Copy Number Variation and Susceptibility to HIV-1 Infection: A Meta-Analysis|journal=PLoS ONE|volume=5|issue=12|year=2010|pages=e15778|issn=1932-6203|doi=10.1371/journal.pone.0015778}}</ref><ref name="Usher2015" />
+dPCR was designed to measure the concentration of a nucleic acid target in copies per unit volume of the sample. When operating in dilute reactions where less than ~10% of the partitions contain a desired target (referred to as “limiting dilution”), copy number can be estimated by comparing the number of fluorescent droplets arising from a target CNV with the number of fluorescent droplets arising from an invariant single-copy reference locus.<ref name="Bell2018" /> In fact, both at these lower target concentrations and at higher ones where multiple copies of the same target can co-localize to a single partition, [[Poisson distribution|Poisson statistics]] are used to correct for these multiple occupancies to give a more accurate value for each target’s concentration.<ref name="Pinheiro2018">{{cite journal|last1=Pinheiro|first1=Leonardo|last2=Emslie|first2=Kerry R.|title=Basic Concepts and Validation of Digital PCR Measurements|volume=1768|year=2018|pages=11–24|issn=1064-3745|doi=10.1007/978-1-4939-7778-9_2}}</ref><ref name="Quan2018">{{cite journal|last1=Quan|first1=Phenix-Lan|last2=Sauzade|first2=Martin|last3=Brouzes|first3=Eric|title=dPCR: A Technology Review|journal=Sensors|volume=18|issue=4|year=2018|pages=1271|issn=1424-8220|doi=10.3390/s18041271}}</ref>
+Digital PCR has been used to uncover both germline and somatic variation in gene copy number between humans<ref name="HandsakerVan Doren2015">{{cite journal|last1=Handsaker|first1=Robert E|display-authors=et al|title=Large multiallelic copy number variations in humans|journal=Nature Genetics|volume=47|issue=3|year=2015|pages=296–303|issn=1061-4036|doi=10.1038/ng.3200}}</ref> and to study the link between amplification of [[HER2/neu|HER2]] (ERBB2) and [[breast cancer]] progression.<ref name="Garcia-MurillasTurner2018">{{cite journal|last1=Garcia-Murillas|first1=Isaac|last2=Turner|first2=Nicholas C.|title=Assessing HER2 Amplification in Plasma cfDNA|volume=1768|year=2018|pages=161–172|issn=1064-3745|doi=10.1007/978-1-4939-7778-9_10}}</ref><ref name="Christgenvan Luttikhuizen2016">{{cite journal|last1=Christgen|first1=Matthias|last2=van Luttikhuizen|display-authors=et al|title=Precise <i>ERBB2</i> copy number assessment in breast cancer by means of molecular inversion probe array analysis|journal=Oncotarget|volume=7|issue=50|year=2016|issn=1949-2553|doi=10.18632/oncotarget.12421}}</ref><ref name="BorleyMercer2014">{{cite journal|last1=Borley|first1=A|display-authors=et al|title=Impact of HER2 copy number in IHC2+/FISH-amplified breast cancer on outcome of adjuvant trastuzumab treatment in a large UK cancer network|journal=British Journal of Cancer|volume=110|issue=8|year=2014|pages=2139–2143|issn=0007-0920|doi=10.1038/bjc.2014.147}}</ref><ref name="Gevensleben2013" />
+=== Rare mutation and rare allele detection ===
+Partitioning in digital PCR increases sensitivity and allows for detection of rare events, especially [[single-nucleotide polymorphism|single nucleotide variants]] (SNVs), by isolating or greatly diminishing the target [[biomarker]] signal from potentially competing background.<ref name="HindsonNess2011" /> These events can be organized into two classes: rare mutation detection and rare sequence detection.
+==== Rare Mutation Detection ====
+Rare mutation detection occurs when a biomarker exists within a background of a highly abundant counterpart that differs by only a single nucleotide variant (SNV). Digital PCR has been shown to be capable of detecting mutant DNA in the presence of a 100,000-fold excess of [[wild type]] background, which is 1,000 times more sensitive than achievable with conventional qPCR.<ref name="HindsonNess2011" />
+==== Rare Sequence Detection ====
+Digital PCR can detect rare sequences such as HIV DNA in patients with HIV,<ref name="Strain2013" /> and DNA from fecal bacteria in ocean and other water samples for assessing water quality.<ref name="CaoRaith2015">{{cite journal|last1=Cao|first1=Yiping|last2=Raith|first2=Meredith R.|last3=Griffith|first3=John F.|title=Droplet digital PCR for simultaneous quantification of general and human-associated fecal indicators for water quality assessment|journal=Water Research|volume=70|year=2015|pages=337–349|issn=00431354|doi=10.1016/j.watres.2014.12.008}}</ref> dPCR can detect sequences as rare as 1 in every 1,250,000 cells.<ref name="Strain2013" />
+==== Liquid Biopsy ====
+dPCR’s ability to detect rare mutations may be of particular benefit in the clinic through the use of the [[liquid biopsy]], a generally noninvasive strategy for detecting and monitoring disease via bodily fluids.<ref name="Skibo" /><ref name="ESMO2017">{{cite news |last=European Society for Medical Oncology |date=17 Nov 2017 |title= Study analyzes mutations in cerebrospinal fluid in lung cancer with brain metastases|url=https://medicalxpress.com/news/2017-11-mutations-cerebrospinal-fluid-lung-cancer.html |access-date=24 July 2019}}</ref> Researchers have used liquid biopsy to monitor tumor load, treatment response and disease progression in [[cancer]] patients by measuring rare mutations in [[circulating tumor DNA]] (ctDNA) in a variety of biological fluids from patients including [[blood]], [[urine]] and [[cerebrospinal fluid]].<ref name="Skibo" /><ref name="GWPetrone">{{cite news |last=Petrone |first=Justin |date=8 Jun 2017 |title= Norwegian Team Plans to Debut Digital PCR-Based Urinary Bladder Cancer Test by Year End
+|url=https://www.genomeweb.com/molecular-diagnostics/norwegian-team-plans-debut-digital-pcr-based-urinary-bladder-cancer-test-year |access-date=24 July 2019}}</ref><ref name="Hiemcke-Jiwa2018">{{cite journal|last1=Hiemcke-Jiwa|first1=Laura S.|display-authors=et al|title=The use of droplet digital PCR in liquid biopsies: A highly sensitive technique for MYD88 p.(L265P) detection in cerebrospinal fluid|journal=Hematological Oncology|year=2018|doi= 10.1002/hon.2489}}</ref>. Early detection of ctDNA (as in molecular [[relapse]]) may lead to earlier administration of an [[immunotherapy]] or a targeted therapy specific for the patient’s mutation signature, potentially improving chances of the treatment’s effectiveness rather than waiting for clinical relapse before altering treatment. Liquid biopsies can have turnaround times of a few days, compared to two to four weeks or longer for tissue-based tests.<ref name="Paxton2017">{{cite news |last=Paxton |first=Anne |date=Oct 2017 |title= Revived hopes, fresh challenges with liquid biopsy
+|url=https://www.captodayonline.com/revived-hopes-fresh-challenges-liquid-biopsy/ |access-date=24 July 2019}}</ref><ref name="BiodesixCLP">{{cite news |last1=Bhadra |first1=Krish |last2=Mellert|first2=Hestia|last3=Pestano|first3=Gary|date=5 Jun 2017 |title= Adoption of Liquid Biopsy Tests for NSCLC|url=http://www.clpmag.com/2017/06/adoption-liquid-biopsy-tests-nsclc/ |access-date=24 July 2019}}</ref> This reduced time to results has been used by physicians to expedite treatments tailored to [[biopsy]] data.<ref name="Paxton2017" />
+In 2016, a prospective trial using dPCR at the Dana-Farber Cancer Institute authenticated the clinical benefit of liquid biopsy as a predictive diagnostic tool for patients with [[non-small-cell lung cancer]].<ref name="Sacher2016">{{cite journal|last1=Sacher|first1=Adrian G.|last2=Paweletz|first2=Cloud|last3=Dahlberg|first3=Suzanne E.|title=Prospective Validation of Rapid Plasma Genotyping for the Detection of EGFR and KRAS Mutations in Advanced Lung Cancer|journal=JAMA Oncology|volume=2|issue=8|year=2016|pages=1014-1022|doi=10.1001/jamaoncol.2016.0173}}</ref> The application of liquid biopsy tests have also been studied in patients with [[breast cancer|breast]],<ref name="OlssonWinter2015">{{cite journal|last1=Olsson|first1=Eleonor|display-authors=et al|title=Serial monitoring of circulating tumor DNA in patients with primary breast cancer for detection of occult metastatic disease|journal=EMBO Molecular Medicine|volume=7|issue=8|year=2015|pages=1034–1047|issn=1757-4676|doi=10.15252/emmm.201404913}}</ref> [[colorectal cancer|colorectal]],<ref name="CarpinettiDonnard2015">{{cite journal|last1=Carpinetti|first1=Paola|display-authors=et al|title=The use of personalized biomarkers and liquid biopsies to monitor treatment response and disease recurrence in locally advanced rectal cancer after neoadjuvant chemoradiation|journal=Oncotarget|volume=6|issue=35|year=2015|issn=1949-2553|doi=10.18632/oncotarget.5256}}</ref><ref name="ReinertSchøler2016">{{cite journal|last1=Reinert|first1=Thomas|display-authors=et al|title=Analysis of circulating tumour DNA to monitor disease burden following colorectal cancer surgery|journal=Gut|volume=65|issue=4|year=2016|pages=625–634|issn=0017-5749|doi=10.1136/gutjnl-2014-308859}}</ref> [[gynecologic oncology|gynecologic]],<ref name="SamimiPereira2015">{{cite journal|last1=Samimi|first1=Goli|display-authors=et al|title=Personalized Circulating Tumor DNA Biomarkers Dynamically Predict Treatment Response and Survival In Gynecologic Cancers|journal=PLOS ONE|volume=10|issue=12|year=2015|pages=e0145754|issn=1932-6203|doi=10.1371/journal.pone.0145754}}</ref> and [[bladder cancer|bladder]] cancers<ref name="GWPetrone" /><ref name="DahmckeSteven2016">{{cite journal|last1=Dahmcke|first1=Christina M.|display-authors=et al|title=A Prospective Blinded Evaluation of Urine-DNA Testing for Detection of Urothelial Bladder Carcinoma in Patients with Gross Hematuria|journal=European Urology|volume=70|issue=6|year=2016|pages=916–919|issn=03022838|doi=10.1016/j.eururo.2016.06.035}}</ref> to monitor both the disease load and the tumor’s response to treatment.
+=== Gene expression and RNA quantification ===
+[[Gene expression]] and [[RNA]] quantification studies have benefited from the increased precision and absolute quantification of dPCR. RNA quantification can be accomplished via [[Reverse transcription polymerase chain reaction|RT-PCR]], wherein RNA is reverse-transcribed into [[Complementary DNA|cDNA]] in the partitioned reaction itself, and the number of RNA molecules originating from each transcript (or allelic transcript) is quantified via dPCR (ref).<ref name="Kamitaki2018" />
+One can often achieve greater sensitivity and precision by using dPCR rather than qPCR to quantify RNA molecules in part because it does not require use of a standard curve for quantification.<ref name="Taylor2015">{{cite journal|last1=Taylor|first1=Sean S.|display-authors=et al|title=Optimization of Droplet Digital PCR from RNA and DNA extracts with direct comparison to RT-qPCR: Clinical implications for quantification of Oseltamivir-resistant subpopulations|journal= Journal of Virological Methods |volume=224|year=2015|pages=58–66|doi=10.1016/j.jviromet.2015.08.014}}</ref> dPCR is also more resilient to PCR inhibitors for the quantification of RNA than qPCR.<ref name="RačkiDreo2014" /><ref name="StauberShaikh2016" />
+dPCR can detect and quantify more individual target species per detection channel than qPCR by virtue of being able to distinguish targets based on their differential fluorescence amplitude or by the use of distinctive color combinations for their detection.<ref name="WhaleHuggett2016">{{cite journal|last1=Whale|first1=Alexandra S.|last2=Huggett|first2=Jim F.|last3=Tzonev|first3=Svilen|title=Fundamentals of multiplexing with digital PCR|journal=Biomolecular Detection and Quantification|volume=10|year=2016|pages=15–23|issn=22147535|doi=10.1016/j.bdq.2016.05.002}}</ref> As an example of this, a 2-channel dPCR system has been used to detect in a single well the expression of four different splice variants of human [[telomerase reverse transcriptase]], a protein that is more active in most tumor cells than in healthy cells.<ref name="Sun2014">{{cite journal|last1=Sun|first1=Bing|last2=Tao|first2=Lian|last3=Zheng|first3=Yung-Ling|title=Simultaneous quantification of alternatively spliced transcripts in a single droplet digital PCR reaction|journal=Biotechniques|volume=56|year=2014|pages=319–325|doi=10.2144/000114179}}</ref>
+=== Alternative Uses for Partitioning ===
+Using the dynamic partitioning capabilities employed in dPCR, improved NGS sequencing can be achieved by partitioning of complex PCR reactions prior to amplification to give more uniform amplification across many distinct [[amplicons]] for [massive parallel sequencing|NGS]] analysis.<ref name="ValenciaRhodenizer2012">{{cite journal|last1=Valencia|first1=C. Alexander|display-authors=et al|title=Assessment of Target Enrichment Platforms Using Massively Parallel Sequencing for the Mutation Detection for Congenital Muscular Dystrophy|journal=The Journal of Molecular Diagnostics|volume=14|issue=3|year=2012|pages=233–246|issn=15251578|doi=10.1016/j.jmoldx.2012.01.009}}</ref><ref name="BrusgaardPhilippe2015">{{cite journal|last1=Brusgaard|first1=Klaus|display-authors=et al|title=What Is the Best NGS Enrichment Method for the Molecular Diagnosis of Monogenic Diabetes and Obesity?|journal=PLOS ONE |volume=10 |issue=11 |year=2015 |pages=e0143373|issn=1932-6203|doi=10.1371/journal.pone.0143373}}</ref> Additionally, the improved specificity of complex PCR amplification reactions in droplets has been shown to greatly reduce the number of iterations required to select for high affinity [[aptamers]] in the [[Systematic evolution of ligands by exponential enrichment|SELEX]] method.<ref name="OuelletFoley2015">{{cite journal|last1=Ouellet|first1=Eric|display-authors=et al|title=Hi-Fi SELEX: A high-fidelity digital-PCR based therapeutic aptamer discovery platform|journal=Biotechnology and Bioengineering |volume=112 |issue=8|year=2015|pages=1506–1522|issn=00063592|doi=10.1002/bit.25581}}</ref> Partitioning can also allow for more robust measurements of telomerase activity from cell lysates.<ref name="LudlowShelton2018">{{cite journal|last1=Ludlow|first1=Andrew T.|display-authors=et al|title=ddTRAP: A Method for Sensitive and Precise Quantification of Telomerase Activity|volume=1768|year=2018|pages=513–529|issn=1064-3745|doi=10.1007/978-1-4939-7778-9_29}}</ref><ref name="SayedSlusher2019">{{cite journal|last1=Sayed|first1=Mohammed E.|last2=Slusher|first2=Aaron L.|last3=Ludlow|first3=Andrew T.|title=Droplet Digital TRAP (ddTRAP): Adaptation of the Telomere Repeat Amplification Protocol to Droplet Digital Polymerase Chain Reaction|journal=Journal of Visualized Experiments|issue=147|year=2019|issn=1940-087X|doi=10.3791/59550}}</ref>
+=== Droplet Digital PCR ===
+In Droplet Digital PCR (ddPCR), a 20 microliter sample reaction including assay primers and either Taqman probes or an intercalating dye, is divided into ~20,000 nanoliter-sized oil droplets through a water-oil [[emulsion]] technique, thermocycled to endpoint in a 96-well PCR plate, and fluorescence amplitude read for all droplets in each sample well in a droplet flow cytometer.<ref name="HindsonNess2011" /><ref name="Pinheiro2012">{{cite journal | vauthors = Pinheiro LB, Coleman VA, Hindson CM, Herrmann J, Hindson BJ, Bhat S, Emslie KR | title = Evaluation of a droplet digital polymerase chain reaction format for DNA copy number quantification | journal = Analytical Chemistry | volume = 84 | issue = 2 | pages = 1003–11 | date = January 2012 | pmid = 22122760 | pmc = 3260738 | doi = 10.1021/ac202578x | doi-access = free }}</ref><ref name="Wood-BouwensJi2018">{{cite journal|last1=Wood-Bouwens|first1=Christina M.|last2=Ji|first2=Hanlee P.|title=Single Color Multiplexed ddPCR Copy Number Measurements and Single Nucleotide Variant Genotyping|volume=1768|year=2018|pages=323–333|issn=1064-3745|doi=10.1007/978-1-4939-7778-9_18}}</ref>
 == History ==