A survey of tools for the analysis of quantitative PCR (qPCR) data <s> Copy number variations (CNV) <s> Background ::: As compared with traditional transgene copy number detection technologies such as Southern blot analysis, real-time PCR provides a fast, inexpensive and high-throughput alternative. However, the real-time PCR based transgene copy number estimation tends to be ambiguous and subjective stemming from the lack of proper statistical analysis and data quality control to render a reliable estimation of copy number with a prediction value. Despite the recent progresses in statistical analysis of real-time PCR, few publications have integrated these advancements in real-time PCR based transgene copy number determination. <s> BIB001 </s> A survey of tools for the analysis of quantitative PCR (qPCR) data <s> Copy number variations (CNV) <s> This paper assesses the quantitative resolution of qPCR using copy number variation (CNV) as a paradigm. An error model is developed for real-time qPCR data showing how the precision of CNV determination varies with the number of replicates. Using samples with varying numbers of X chromosomes, experimental data demonstrates that real-time qPCR can readily distinguish four copes from five copies, which corresponds to a 1.25-fold difference in relative quantity. Digital PCR is considered as an alternative form of qPCR. For digital PCR, an error model is shown that relates the precision of CNV determination to the number of reaction chambers. The quantitative capability of digital PCR is illustrated with an experiment distinguishing four and five copies of the human gene MRGPRX1. For either real-time qPCR or digital PCR, practical application of these models to achieve enhanced quantitative resolution requires use of a high throughput PCR platform that can simultaneously perform thousands of reactions. Comparing the two methods, real-time qPCR has the advantage of throughput and digital PCR has the advantage of simplicity in terms of the assumptions made for data analysis. <s> BIB002 </s> A survey of tools for the analysis of quantitative PCR (qPCR) data <s> Copy number variations (CNV) <s> Copy number changes are known to be involved in numerous human genetic disorders. In this context, qPCR-based copy number screening may serve as the method of choice for targeted screening of the relevant disease genes and their surrounding regulatory landscapes. qPCR has many advantages over alternative methods, such as its low consumable and instrumentation costs, fast turnaround and assay development time, high sensitivity and open format (independent of a single supplier). In this chapter we provide all relevant information for a successfully implement of qPCR-based copy number analysis. We emphasize the significance of thorough in silico and empirical validation of the primers, the need for a well thought-out experiment design, and the importance of quality controls along the entire workflow. Furthermore, we suggest an appropriate and practical way to calculate copy numbers and to objectively interpret the results. The provided guidelines will most certainly improve the quality and reliability of your qPCR-based copy number screening. <s> BIB003 </s> A survey of tools for the analysis of quantitative PCR (qPCR) data <s> Copy number variations (CNV) <s> Inter-individual genomic variations have recently become evident with advances in sequencing techniques and genome-wide array comparative genomic hybridization. Among such variations single nucleotide polymorphisms (SNPs) are widely studied and better defined because of availability of large-scale detection platforms. However, insertion-deletions, inversions, copy-number variations (CNVs) also populate our genomes. The large structural variations (>3 Mb) have been known for past 20 years, however, their link to health and disease remain ill-defined. CNVs are defined as the segment of DNA >1 kb in size, and compared with reference genome vary in its copy number. All these types of genomic variations are bound to have vital role in disease susceptibility and drug response. In this review, the discussion is confined to CNVs and their link to health, diseases and drug response. There are several CNVs reported till date, which have important roles in an individual's susceptibility to several complex and common disorders. This review compiles some of these CNVs and analyzes their involvement in diseases in different populations, analyses available evidence and rationalizes their involvement in the development of disease phenotype. Combined with SNP, additional genomic variations including CNV, will provide better correlations between individual genomic variations and health. <s> BIB004 </s> A survey of tools for the analysis of quantitative PCR (qPCR) data <s> Copy number variations (CNV) <s> Quantitative real-time PCR is PCR visualized in real time by the use of fluorescent or intercalating dyes, which are employed to measure gene expression or gene quantification including contiguous gene deletions or duplications. A simple method is described here to quantify DNA copy number from human samples. <s> BIB005 </s> A survey of tools for the analysis of quantitative PCR (qPCR) data <s> Copy number variations (CNV) <s> The analysis of quantitative PCR data usually does not take into account the fact that the increase in fluorescence depends on the monitoring chemistry, the input of ds-DNA or ss-cDNA, and the directionality of the targeting of probes or primers. The monitoring chemistries currently available can be categorized into six groups: (A) DNA-binding dyes; (B) hybridization probes; (C) hydrolysis probes; (D) LUX primers; (E) hairpin primers; and (F) the QZyme system. We have determined the kinetics of the increase in fluorescence for each of these groups with respect to the input of both ds-DNA and ss-cDNA. For the latter, we also evaluated mRNA and cDNA targeting probes or primers. This analysis revealed three situations. Hydrolysis probes and LUX primers, compared to DNA-binding dyes, do not require a correction of the observed quantification cycle. Hybridization probes and hairpin primers require a correction of −1 cycle (dubbed C-lag), while the QZyme system requires the C-lag correction and an efficiency-dependent C-shift correction. A PCR efficiency value can be derived from the relative increase in fluorescence in the exponential phase of the amplification curve for all monitoring chemistries. In case of hydrolysis probes, LUX primers and hairpin primers, however, this should be performed after cycle 12, and for the QZyme system after cycle 19, to keep the overestimation of the PCR efficiency below 0.5 %. Figure The qPCR monitoring chemistries form six groups with distinct fluorescence kinetics. The displacement of the amplification curve depends on the chemistry, DNA input and probe-targeting. The observed shift in Cq values can be corrected and PCR efficiencies can be derived. The qPCR monitoring chemistries form six groups with distinct fluorescence kinetics. The displacement of the amplification curve depends on the chemistry, DNA input and probe-targeting. The observed shift in Cq values can be corrected and PCR efficiencies can be derived. <s> BIB006
The gene copy number is the number of copies of a particular gene in the genotype of an individual, e.g., diploid genomes usually possess two copies of each gene. Copy number variations (CNVs) in the genome are genetic variations where segments of DNA are present in a variable number of copies in comparison to the reference (e.g., diploid human) genome. CNVs can arise by a variety of processes, such as deletions, duplications and translocations during meiosis. They may influence both mRNA and protein levels and have recently been associated with several complex and common diseases BIB004 . The experimental setup and statistical methods to calculate copy number variations have been made accessible and were widely applied for studying CNVs in various diseases BIB005 BIB002 BIB001 . By using qPCR, the Cq values of the target gene can be compared to unrelated reference sequences. It has been shown that including multiple reference samples results in more accurate results. Furthermore, it allows combining references with a normal copy number and references with a known CNV, which can serve as reference point and as positive control for the detection of CNVs BIB003 . The generated Cq values are then used for CNV calculation. As Other (5) R (9) Web (5) Windows (8) Cq calculation (4) Quantification (abs) (5) Quantification (rel) BIB006 Quantification (both) (2) Normalization (1) dPCR (1) CNV (1) a consequence, methods that support quantification analysis are applicable for CNV calculations BIB003 .