 Data
Analysis and
BioInformatics in
real-time qPCR
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Reference gene with Genevestigator
Genevestigator is a high quality and manually curated expression database and meta-analysis system. It allows biologists to study the expression and regulation of genes in a broad variety of contexts by summarizing information from hundreds of microarray experiments into easily interpretable results. A user-friendly interface allows you to visualize gene expression in many different tissues, at multiple developmental stages, or in response to large sets of stimuli, diseases, drug treatments, or genetic modifications. This type of meta-analysis is core to understanding the spatio-temporal-response regulation of genes, to identify or validate biomarkers, and to find out which subnetworks are commonly affected in different diseases and conditions. Real-time PCR gene expression profiling
Mikael Kubista, Björn Sjögreen, Amin Forootan, Radek Sindelka and Jiri Jonák, and José Manuel Andrade Real-time PCR has rapidly become the preferred technique for quantitative analysis of nucleic acids. Its superior sensitivity, reproducibility and dynamic range make it the preferred choice for expression profiling in scientific, as well as routine, applications. => Link to GenEx software Real-Time PCR: Current Technology and Applications http://www.horizonpress.com/realtimepcr
Publisher: Caister Academic Press Editor: Julie Logan, Kirstin Edwards and Nick Saunders Applied and Functional Genomics, Health Protection Agency, London (2009) ISBN: 978-1-904455-39-4 Price: GB £150 or US $310 (hardback). Pages: x + 284 (plus colour plates) Chapter 4 - Reference Gene Validation Software for Improved Normalization J. Vandesompele, M. Kubista and M. W. Pfaffl (2009) Real-time PCR is the method of choice for expression analysis of a limited number of genes. The measured gene expression variation between subjects is the sum of the true biological variation and several confounding factors resulting in non-specific variation. The purpose of normalization is to remove the non-biological variation as much as possible. Several normalization strategies have been proposed, but the use of one or more reference genes is currently the preferred way of normalization. While these reference genes constitute the best possible normalizers, a major problem is that these genes have no constant expression under all experimental conditions. The experimenter therefore needs to carefully assess whether a certain reference gene is stably expressed in the experimental system under study. This is not trivial and represents a circular problem. Fortunately, several algorithms and freely available software have been developed to address this problem. This chapter aims to provide an overview of the different concepts. Chapter 5 - Data Analysis Software M. W. Pfaffl, J. Vandesompele and M. Kubista (2009) Quantitative real-time RT-PCR (qRT-PCR) is widely and increasingly used in any kind of mRNA quantification, because of its high sensitivity, good reproducibility and wide dynamic quantification range. While qRT-PCR has a tremendous potential for analytical and quantitative applications, a comprehensive understanding of its underlying principles is important. Beside the classical RT-PCR parameters, e.g. primer design, RNA quality, RT and polymerase performances, the fidelity of the quantification process is highly dependent on a valid data analysis. This review will cover all aspects of data acquisition (trueness, reproducibility, and robustness), potentials in data modification and will focus particularly on relative quantification methods. Furthermore useful bioinformatical, biostatical as well as multi-dimensional expression software tools will be presented. Real-Time PCR:
Current Technology and Applications - Book reviews:
"... a useful book for students ..." from J. Microbiological Methods "provides
a dual
focus by aiming, in
the early chapters, to provide both the theory and practicalities of
this diverse and superficially simple technology, counter-balancing
this in the later chapters with real-world applications, covering
infectious diseases, biodefence, molecular haplotyping and food
standards." from Microbiology
Today
"a
reference work
that should be found both in university libraries and on the shelves of
experienced applications specialists." from Microbiology
Today
"a comprehensive guide to real-time PCR technology and its applications" from Food Science and Technology Abstracts (2009) Volume 41 Number 6 "This
volume
should be of utmost
interest to all investigators interested and involved in using RT-PCR
... the RT-PCR protocols covered in this book will be of interest to
most, if not all, investigators engaged in research that uses this
important technique ... a well balanced book covering the many
potential uses of real-time PCR ... valuable for all those interested
in RT-PCR." from Doodys
reviews (2009)
"provide
the
novice and the experienced user with guidance on the technology, its
instrumentation, and its applications" f rom SciTech Book News
2009 p. 64
"... written by international authors expert in specific technical principles and applications ... a useful compendium of basic and advanced applications for laboratory scientists. It is an ideal introductory textbook and will serve as a practical handbook in laboratories where the technology is employed." from Christopher J. McIver, Microbiology Department, Prince of Wales Hospital, New South Wales, Australia writing in Australian J. Med. Sci. 2009. 30(2): 59-60
Statistical
analysis of real-time PCR data.
Yuan JS, Reed A, Chen F, Stewart CN Jr. BMC Bioinformatics. 2006 (7): 85. Department of Plant Sciences, University of Tennessee, Knoxville, TN 37996, USA. BACKGROUND: Even though real-time PCR has been broadly applied in biomedical sciences, data processing procedures for the analysis of quantitative real-time PCR are still lacking; specifically in the realm of appropriate statistical treatment. Confidence interval and statistical significance considerations are not explicit in many of the current data analysis approaches. Based on the standard curve method and other useful data analysis methods, we present and compare four statistical approaches and models for the analysis of real-time PCR data. RESULTS: In the first approach, a multiple regression analysis model was developed to derive DeltaDeltaCt from estimation of interaction of gene and treatment effects. In the second approach, an ANCOVA (analysis of covariance) model was proposed, and the DeltaDeltaCt can be derived from analysis of effects of variables. The other two models involve calculation DeltaCt followed by a two group t-test and non-parametric analogous Wilcoxon test. SAS programs were developed for all four models and data output for analysis of a sample set are presented. In addition, a data quality control model was developed and implemented using SAS. CONCLUSION: Practical statistical solutions with SAS programs were developed for real-time PCR data and a sample dataset was analyzed with the SAS programs. The analysis using the various models and programs yielded similar results. Data quality control and analysis procedures presented here provide statistical elements for the estimation of the relative expression of genes using real-time PCR. Data
Analysis Methods
There are two methods, both equally valid, for analyzing data obtained from real time PCR: Relative Standard Curve Method and Comparative CT Method. The first, relative standard curve method, is useful for investigators that have a limited number of cDNA samples and a large number of genes of interest. The comparative CT method is useful for investigators who have a lage number of cDNA samples and a limited number of genes of interest (RRC Core Genomics Facility, University of Illinois at Chicago) qPCR
Bioinformatik: Neue Entwicklungen in der post-qPCR
Datenanalyse (in German)
Michael W. Pfaffl (2006), Laborwelt (1): 10-13, ISSN 1611–0854 (Editor: T. Gabrielczyk) Die Entwicklung der Polymerase Ketten Reaktion (PCR) in den 80er Jahren gehört zweifelsohne zu den größten Errungenschaften in der Molekularbiologie. Mittels der klassischen PCR lassen sich hochsensitiv Genabschnitte oder DNA Fragmente qualitativ sowie semi-quantitativ nachweisen. Um spezifische mRNA zu quantifizieren, stellt man der PCR die Reverse Transkription (RT) vor. Die Anwendung der RT-PCR zur Quantifizierung spezifischen mRNA ist heute zum Routinewerkzeug in der Expressionsanalytik geworden. Die gewonnenen Ergebnisse sind von überproportionalen Nutzen in der molekularbiologischen Forschung und molekularen Diagnostik, in der vergleichenden Expressionsanalytik sowie zur Aufklärung der „Functional Genomics“. Der Nachweis kann qualitativ in klassischen Thermocyclern oder in „real-time“ quantitativ mittels Echtzeit PCR (qPCR) durchgeführt werden. Die Ergebnisse sind direkt verfügbar, so dass der Einsatz der qPCR eine deutliche Zeitersparnis mit sich bringt. Da die Zunahme der Fluoreszenz und die Menge an neusynthetisierten PCR-Produkten über einen weiten Bereich proportional zueinander sind, kann aus den gewonnenen Fluoreszenzdaten die eingesetzte Ausgangsmenge der DNA respektive RNA bestimmt werden. Vorraussetzung für einen zuverlässigen quantitativen Nachweis ist eine funktionierende Analytik und Datenauswertung, die exakte Quantifizierungsergebnisse bei ausreichender Genauigkeit und hoher Wiederholbarkeit liefert. QPCR DEMO -
real-time PCR data management and analysis
Developed by - Stephan Pabinger http://genome.tugraz.at/QPCR or https://esus.genome.tugraz.at/rtpcr QPCR is a versatile web-based Java application that allows to store, manage, analyze, and display data from quantitative real-time polymerase chain reaction (qPCR) experiments. You can try out the application by using the demo account at QPCR Demo It is strongly recommended to use a private account which guarantees confidentiality and security of your data. To request an account please contact qpcr@genome.tugraz.at To get started: Read the tutorial which leads you through all important steps of the application. For more information download the user guide which covers all aspects of the application. QPCR: Application for real-time PCR data
management and analysis.
Pabinger S, Thallinger GG, Snajder R, Eichhorn H, Rader R, Trajanoski Z. BMC Bioinformatics 2009, 10:268 BACKGROUND: Since its introduction quantitative real-time polymerase chain reaction (qPCR) has become the standard method for quantification of gene expression. Its high sensitivity, large dynamic range, and accuracy led to the development of numerous applications with an increasing number of samples to be analyzed. Data analysis consists of a number of steps, which have to be carried out in several different applications. Currently, no single tool is available which incorporates storage, management, and multiple methods covering the complete analysis pipeline. RESULTS: QPCR is a versatile web-based Java application that allows to store, manage, and analyze data from relative quantification qPCR experiments. It comprises a parser to import generated data from qPCR instruments and includes a variety of analysis methods to calculate cycle-threshold and amplification efficiency values. The analysis pipeline includes technical and biological replicate handling, incorporation of sample or gene specific efficiency, normalization using single or multiple reference genes, inter-run calibration, and fold change calculation. Moreover, the application supports assessment of error propagation throughout all analysis steps and allows conducting statistical tests on biological replicates. Results can be visualized in customizable charts and exported for further investigation. CONCLUSION: We have developed a web-based system designed to enhance and facilitate the analysis of qPCR experiments. It covers the complete analysis workflow combining parsing, analysis, and generation of charts into one single application. The system is freely available at http://genome.tugraz.at/QPCR 
 The
qpcR library - Analysis
of real-time PCR data using R
The qpcR library is an extension to the R environment that assists in the modelling and analysis of quantitative real-time PCR data => http://www.dr-spiess.de/qpcR.html With the qpcR library you can:
 PowerNest - illuminating error in qPCR experiment design
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