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      qBase relative quantification framework and software for management and automated analysis of real-time quantitative PCR data

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          Abstract

          qBase, a free program for the management and automated analysis of qPCR data, is described

          Abstract

          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.

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          Error propagation in relative real-time reverse transcription polymerase chain reaction quantification models: the balance between accuracy and precision.

          Real-time reverse transcription polymerase chain reaction (RT-PCR) has gained wide popularity as a sensitive and reliable technique for mRNA quantification. The development of new mathematical models for such quantifications has generally paid little attention to the aspect of error propagation. In this study we evaluate, both theoretically and experimentally, several recent models for relative real-time RT-PCR quantification of mRNA with respect to random error accumulation. We present error propagation expressions for the most common quantification models and discuss the influence of the various components on the total random error. Normalization against a calibrator sample to improve comparability between different runs is shown to increase the overall random error in our system. On the other hand, normalization against multiple reference genes, introduced to improve accuracy, does not increase error propagation compared to normalization against a single reference gene. Finally, we present evidence that sample-specific amplification efficiencies determined from individual amplification curves primarily increase the random error of real-time RT-PCR quantifications and should be avoided. Our data emphasize that the gain of accuracy associated with new quantification models should be validated against the corresponding loss of precision.
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            Normalization of real-time quantitative reverse transcription-PCR data : a model-based variance estimation approach to identify genes suited for normalization, applied to bladder and colon cancer data sets

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              Rapid detection of VHL exon deletions using real-time quantitative PCR.

              Various types of mutations exist that exert an effect on the normal function of a gene. Among these, exon/gene deletions often remain unnoticed in initial mutation screening. Until recently, no fast and efficient methods were available to detect this type of mutation. Molecular detection methods for gene copy number changes included Southern blot (SB) and fluorescence in situ hybridisation, both with their own intrinsic limitations. In this paper, we report the development and application of a fast, sensitive and high-resolution method for the detection of single exon or larger deletions in the VHL gene based on real-time quantitative PCR (Q-PCR). These deletions account for approximately one-fifth of all patients with the von Hippel-Lindau syndrome, a dominantly inherited highly penetrant familial cancer syndrome predisposing to specific malignancies including phaeochromocytomas and haemangioblastomas. Our VHL exon quantification strategy is based on SYBR Green I detection and normalisation using two reference genes with a normal copy number, that is, ZNF80 (3q13.31) and GPR15 (3q12.1). Choice of primer sequences and the use of two reference genes appears to be critical for accurate discrimination between 1 and 2 exon copies. In a blind Q-PCR study of 29 samples, all 14 deletions were detected, which is in perfect agreement with previously determined SB results. We propose Q-PCR as the method of choice for fast (within 3.5 h), accurate and sensitive (ng amount of input DNA) exon deletion screening in routine DNA diagnosis of VHL disease. Similar assays can be designed for deletion screening in other genetic disorders.
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                Author and article information

                Journal
                Genome Biol
                Genome Biology
                BioMed Central (London )
                1465-6906
                1465-6914
                2007
                9 February 2007
                : 8
                : 2
                : R19
                Affiliations
                [1 ]Center for Medical Genetics, Ghent University Hospital, De Pintelaan, B-9000 Ghent, Belgium
                Article
                gb-2007-8-2-r19
                10.1186/gb-2007-8-2-r19
                1852402
                17291332
                7607ea95-977b-4097-8bd5-3a269474afa6
                Copyright © 2007 Hellemans et al.; licensee BioMed Central Ltd.

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                Categories
                Method

                Genetics
                Genetics

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