A survey of tools for the analysis of quantitative PCR (qPCR) data <s> Other platforms <s> Although quantitative PCR (qPCR) is becoming the method of choice for expression profiling of selected genes, accurate and straightforward processing of the raw measurements remains a major hurdle. Here we outline advanced and universally applicable models for relative quantification and inter-run calibration with proper error propagation along the entire calculation track. These models and algorithms are implemented in qBase, a free program for the management and automated analysis of qPCR data. <s> BIB001 </s> A survey of tools for the analysis of quantitative PCR (qPCR) data <s> Other platforms <s> BackgroundBased upon defining a common reference point, current real-time quantitative PCR technologies compare relative differences in amplification profile position. As such, absolute quantification requires construction of target-specific standard curves that are highly resource intensive and prone to introducing quantitative errors. Sigmoidal modeling using nonlinear regression has previously demonstrated that absolute quantification can be accomplished without standard curves; however, quantitative errors caused by distortions within the plateau phase have impeded effective implementation of this alternative approach.ResultsRecognition that amplification rate is linearly correlated to amplicon quantity led to the derivation of two sigmoid functions that allow target quantification via linear regression analysis. In addition to circumventing quantitative errors produced by plateau distortions, this approach allows the amplification efficiency within individual amplification reactions to be determined. Absolute quantification is accomplished by first converting individual fluorescence readings into target quantity expressed in fluorescence units, followed by conversion into the number of target molecules via optical calibration. Founded upon expressing reaction fluorescence in relation to amplicon DNA mass, a seminal element of this study was to implement optical calibration using lambda gDNA as a universal quantitative standard. Not only does this eliminate the need to prepare target-specific quantitative standards, it relegates establishment of quantitative scale to a single, highly defined entity. The quantitative competency of this approach was assessed by exploiting "limiting dilution assay" for absolute quantification, which provided an independent gold standard from which to verify quantitative accuracy. This yielded substantive corroborating evidence that absolute accuracies of ± 25% can be routinely achieved. Comparison with the LinReg and Miner automated qPCR data processing packages further demonstrated the superior performance of this kinetic-based methodology.ConclusionCalled "linear regression of efficiency" or LRE, this novel kinetic approach confers the ability to conduct high-capacity absolute quantification with unprecedented quality control capabilities. The computational simplicity and recursive nature of LRE quantification also makes it amenable to software implementation, as demonstrated by a prototypic Java program that automates data analysis. This in turn introduces the prospect of conducting absolute quantification with little additional effort beyond that required for the preparation of the amplification reactions. <s> BIB002
Deconvolution is a Perl based program for the efficiencyindependent absolute quantification of qPCR data. The method depends on a computer-assisted deconvolution that determines amplification behavior between the unknown template and an amplicon standard. Deconvolution has been released in 2010, uses raw fluorescence values (before baseline subtraction) and outputs quantification results in text format. LRE Analyzer is a Java-based, standalone, platform independent desktop application offering automated analysis and data storage capabilities. It presents a state-of-the art graphical interface and uses Microsoft Excel for import of raw fluorescence data (before baseline subtraction). The application allows users to conduct absolute quantification without construction of target-specific standard curves. Quantification results are presented in fluorescence units or in target molecules if a known quantity is amplified and used as a reference. The application allows users to visualize the raw fluorescence curve. The MATLAB based tool LRE Analysis is based on the published LRE method BIB002 . It reads raw fluorescence values (after baseline subtraction) from an Excel file that needs to comply with a specific format. Currently, it supports one ABI system and performs data processing in a semi-automated way. Quantification results are exported in a new Excel file containing calculated values. pyQPCR is a Python based application that provides a modern graphical user interface. It takes Cq values as input and supports data import from a few Eppendorf and ABI systems file formats. The methods implemented in pyQPCR are based on qBase BIB001 , and the application is able to perform relative quantification and determination of efficiencies using standard curve calculation. Quantification results can be displayed as bar plots. SASqPCR is a program that requires the commercial SAS software suite, but according to the authors extensive SAS programming knowledge is not required. The tool performs calculations on Cq values and incorporates functions for assessment of PCR efficiencies, validation of reference genes, and normalization using multiple reference genes. Furthermore, SASqPCR provides methods for the statistical comparisons of target gene expression of parallel samples.