A survey of tools for the analysis of quantitative PCR (qPCR) data <s> DNA quantification strategies <s> Rapid cycle DNA amplification was continuously monitored by three different fluorescence techniques. Fluorescence was monitored by (i) the double-strand-specific dye SYBR Green I, (ii) a decrease in fluorescein quenching by rhodamine after exonuclease cleavage of a dual-labeled hydrolysis probe and (iii) resonance energy transfer of fluorescein to Cy5 by adjacent hybridization probes. Fluorescence data acquired once per cycle provides rapid absolute quantification of initial template copy number. The sensitivity of SYBR Green I detection is limited by nonspecific product formation. Use of a single exonuclease hydrolysis probe or two adjacent hybridization probes offers increasing levels of specificity. In contrast to fluorescence measurement once per cycle, continuous monitoring throughout each cycle monitors the temperature dependence of fluorescence. The cumulative, irreversible signal of hydrolysis probes can be distinguished easily from the temperature-dependent, reversible signal of hybridization probes. By using SYBR Green I, product denaturation, annealing and extension can be followed within each cycle. Substantial product-to-product annealing occurs during later amplification cycles, suggesting that product annealing is a major cause of the plateau effect. Continuous within-cycle monitoring allows rapid optimization of amplification conditions and should be particularly useful in developing new, standardized clinical assays. <s> BIB001 </s> A survey of tools for the analysis of quantitative PCR (qPCR) data <s> DNA quantification strategies <s> The ability to multiplex PCR by probe color and melting temperature (Tm) greatly expands the power of real-time analysis. Simple hybridization probes with only a single fluorescent dye can be used for quantification and allele typing. Different probes are labeled with dyes that have unique emission spectra. Spectral data are collected with discrete optics or dispersed onto an array for detection. Spectral overlap between dyes is corrected by using pure dye spectra to deconvolute the experimental data by matrix algebra. Since fluorescence is temperature dependent and depends on the dye, spectral overlap and color compensation constants are also temperature dependent. Single-labeled probes are easier to synthesize and purify than more complex probes with two or more dyes. In addition, the fluorescence of single-labeled probes is reversible and depends only on hybridization of the probe to the target, allowing study of the melting characteristics of the probe. Although melting curves can be obtained during PCR, data are usually acquired at near-equilibrium rates of 0.05–0.2°C/s after PCR is complete. Using rapid-cycle PCR, amplification requires about 20 min followed by a 10-min melting curve, greatly reducing result turnaround time. In addition to dye color, melting temperature can be used for a second dimension of multiplexing. Multiplexing by color and Tm creates a “virtual” two-dimensional multiplexing array without the need for an immobilized matrix of probes. Instead of physical separation along the X and Y axes, amplification products are identified by different fluorescence spectra and melting characteristics. <s> BIB002 </s> A survey of tools for the analysis of quantitative PCR (qPCR) data <s> DNA quantification strategies <s> The real-time reverse transcription polymerase chain reaction (RT-qPCR) addresses the evident requirement for quantitative data analysis in molecular medicine, biotechnology, microbiology and diagnostics and has become the method of choice for the quantification of mRNA. Although it is often described as a "gold" standard, it is far from being a standard assay. The significant problems caused by variability of RNA templates, assay designs and protocols, as well as inappropriate data normalization and inconsistent data analysis, are widely known but also widely disregarded. As a first step towards standardization, we describe a series of RT-qPCR protocols that illustrate the essential technical steps required to generate quantitative data that are reliable and reproducible. We would like to emphasize, however, that RT-qPCR data constitute only a snapshot of information regarding the quantity of a given transcript in a cell or tissue. Any assessment of the biological consequences of variable mRNA levels must include additional information regarding regulatory RNAs, protein levels and protein activity. The entire protocol described here, encompassing all stages from initial assay design to reliable qPCR data analysis, requires approximately 15 h. <s> BIB003 </s> A survey of tools for the analysis of quantitative PCR (qPCR) data <s> DNA quantification strategies <s> RNA transcripts such as mRNA or microRNA are frequently used as biomarkers to determine disease state or response to therapy. Reverse transcription (RT) in combination with quantitative PCR (qPCR) has become the method of choice to quantify small amounts of such RNA molecules. In parallel with the democratization of RT-qPCR and its increasing use in biomedical research or biomarker discovery, we witnessed a growth in the number of gene expression data analysis methods. Most of these methods are based on the principle that the position of the amplification curve with respect to the cycle-axis is a measure for the initial target quantity: the later the curve, the lower the target quantity. However, most methods differ in the mathematical algorithms used to determine this position, as well as in the way the efficiency of the PCR reaction (the fold increase of product per cycle) is determined and applied in the calculations. Moreover, there is dispute about whether the PCR efficiency is constant or continuously decreasing. Together this has lead to the development of different methods to analyze amplification curves. In published comparisons of these methods, available algorithms were typically applied in a restricted or outdated way, which does not do them justice. Therefore, we aimed at development of a framework for robust and unbiased assessment of curve analysis performance whereby various publicly available curve analysis methods were thoroughly compared using a previously published large clinical data set (Vermeulen et al., 2009) [11]. The original developers of these methods applied their algorithms and are co-author on this study. We assessed the curve analysis methods' impact on transcriptional biomarker identification in terms of expression level, statistical significance, and patient-classification accuracy. The concentration series per gene, together with data sets from unpublished technical performance experiments, were analyzed in order to assess the algorithms' precision, bias, and resolution. While large differences exist between methods when considering the technical performance experiments, most methods perform relatively well on the biomarker data. The data and the analysis results per method are made available to serve as benchmark for further development and evaluation of qPCR curve analysis methods (http://qPCRDataMethods.hfrc.nl). <s> BIB004 </s> A survey of tools for the analysis of quantitative PCR (qPCR) data <s> DNA quantification strategies <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> BIB005
The design of a qPCR experiment depends, amongst others, on biological (e.g., studied organism, given biological question) and technical (e.g., available platforms, choice of chemistry, primers) parameters. A thorough guideline and detailed procedures covering the technical setup of a qPCR experiment has been published elsewhere BIB003 . The quantification of target DNA in each cycle of a qPCR experiment is based on measuring the emission of a fluorescent reporter dye. Dyes that bind to double-stranded DNA and upon excitation emit light (e.g., SYBR Green) are the most widely used DNA dyes due to ease of use, cost efficiency, and generic detection BIB001 . Their disadvantage is that they bind to any doublestranded DNA, including non-specific reaction products, which might result in an overestimation of the target concentration. Probe-based methods, such as TaqMan probes, molecular beacons, or scorpion primers rely on the sequence-specific detection of a desired PCR product resulting in increased specificity and sensitivity  BIB005 . Furthermore, different probes can be used for multiplex PCR, in which multiple targets are amplified and detected in a single reaction tube. Unique probes or specific melting temperatures distinguish each PCR target amplified by a different set of primers BIB002 . Multiplex PCR reduces reagent consumption and allows studying more combinations of samples and target genes on one chip, but might reduce sensitivity as targets compete with each other for reaction resources. Currently, up to five different reactions can be detected simultaneously in one tube. Based on the detected fluorescent signal and the chosen experimental setup several analysis steps are needed to obtain biological meaningful results (see Fig. 2 ). First, based on the raw fluorescence values a baseline is subtracted from the raw data, which is a crucial step in qPCR data analysis BIB004 . Next, the quantification cycle (Cq) value -previously known as the threshold cycle (Ct), crossing point (Cp), or take-off point (TOP) -can be calculated. In general, the Cq value represents the number of cycles needed to reach a set threshold fluorescence signal level. In addition, the raw fluorescence values can also be used for inferring the amplification efficiencies. Using the determined Cq value, quantification of nucleic acids can be performed by absolute quantification (via standard curve or digital PCR) or relative quantification (delta Cq)  . Finally, the quantification results can be tested for statistical significant differences and presented in a graphical way.