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      Comparison of microfluidic digital PCR and conventional quantitative PCR for measuring copy number variation

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          Abstract

          One of the benefits of Digital PCR (dPCR) is the potential for unparalleled precision enabling smaller fold change measurements. An example of an assessment that could benefit from such improved precision is the measurement of tumour-associated copy number variation (CNV) in the cell free DNA (cfDNA) fraction of patient blood plasma. To investigate the potential precision of dPCR and compare it with the established technique of quantitative PCR (qPCR), we used breast cancer cell lines to investigate HER2 gene amplification and modelled a range of different CNVs. We showed that, with equal experimental replication, dPCR could measure a smaller CNV than qPCR. As dPCR precision is directly dependent upon both the number of replicate measurements and the template concentration, we also developed a method to assist the design of dPCR experiments for measuring CNV. Using an existing model (based on Poisson and binomial distributions) to derive an expression for the variance inherent in dPCR, we produced a power calculation to define the experimental size required to reliably detect a given fold change at a given template concentration. This work will facilitate any future translation of dPCR to key diagnostic applications, such as cancer diagnostics and analysis of cfDNA.

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          Most cited references 37

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          CNV-seq, a new method to detect copy number variation using high-throughput sequencing

          Background DNA copy number variation (CNV) has been recognized as an important source of genetic variation. Array comparative genomic hybridization (aCGH) is commonly used for CNV detection, but the microarray platform has a number of inherent limitations. Results Here, we describe a method to detect copy number variation using shotgun sequencing, CNV-seq. The method is based on a robust statistical model that describes the complete analysis procedure and allows the computation of essential confidence values for detection of CNV. Our results show that the number of reads, not the length of the reads is the key factor determining the resolution of detection. This favors the next-generation sequencing methods that rapidly produce large amount of short reads. Conclusion Simulation of various sequencing methods with coverage between 0.1× to 8× show overall specificity between 91.7 – 99.9%, and sensitivity between 72.2 – 96.5%. We also show the results for assessment of CNV between two individual human genomes.
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            Circulating nucleic acids (CNAs) and cancer--a survey.

            It has been known for decades that it is possible to detect small amounts of extracellular nucleic acids in plasma and serum of healthy and diseased human beings. The unequivocal proof that part of these circulating nucleic acids (CNAs) is of tumor origin, initiated a surge of studies which confirmed and extended the original observations. In the past few years many experiments showed that tumor-associated alterations can be detected at the DNA and RNA level. At the DNA level the detection of point mutations, microsatellite alterations, chromosomal alterations, i.e. inversion and deletion, and hypermethylation of promoter sequences were demonstrated. At the RNA level the overexpression of tumor-associated genes was shown. These observations laid the foundation for the development of assays for an early detection of cancer as well as for other clinical means.
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              Copy-number variation and association studies of human disease.

              The central goal of human genetics is to understand the inherited basis of human variation in phenotypes, elucidating human physiology, evolution and disease. Rare mutations have been found underlying two thousand mendelian diseases; more recently, it has become possible to assess systematically the contribution of common SNPs to complex disease. The known role of copy-number alterations in sporadic genomic disorders, combined with emerging information about inherited copy-number variation, indicate the importance of systematically assessing copy-number variants (CNVs), including common copy-number polymorphisms (CNPs), in disease. Here we discuss evidence that CNVs affect phenotypes, directions for basic knowledge to support clinical study of CNVs, the challenge of genotyping CNPs in clinical cohorts, the use of SNPs as markers for CNPs and statistical challenges in testing CNVs for association with disease. Critical needs are high-resolution maps of common CNPs and techniques that accurately determine the allelic state of affected individuals.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                June 2012
                June 2012
                28 February 2012
                28 February 2012
                : 40
                : 11
                : e82
                Affiliations
                1LGC Limited, Queens Road, Teddington, Middlesex TW11 0LY, 2Leeds Institute of Molecular Medicine, University of Leeds, St. James’s University Hospital, Leeds LS9 7TF and 3Cancer Studies & Molecular Medicine, University of Leicester, Robert Kilpatrick Clinical Sciences Building, Leicester Royal Infirmary, Leicester LE2 7LX, UK
                Author notes
                *To whom correspondence should be addressed. Tel: +44 20 8943 7655; Fax: +44 20 8943 2767; Email: jim.huggett@ 123456lgcgroup.com
                Article
                gks203
                10.1093/nar/gks203
                3367212
                22373922
                © The Author(s) 2012. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                Page count
                Pages: 9
                Categories
                Methods Online

                Genetics

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