Practical Biostatistics (3 days)
 The objective of this course is to provide an understanding of data processing and statistical methods applicable for analysis of data obtained by real-time PCR. A key ingredient in the course is practical exercises based on real data, including data sets provided by participants. The common experimental designs are introduced and data from such studies are analysed by participants under the supervision of instructors. Throughout the course participants will become familiar with most common experimental cases and self-create excel-based templates for data analysis which they bring home for their own use. In addition, an overview of suitable qPCR software tools will be given.
Biostatistics (1 day)
 This course explains statistics applicable to qPCR and teaches how to use statistics to interpret real-time PCR gene expression data, and classify samples based on real-time PCR expression profiling. Course is based on seminars and computer-based demonstrations. During the course you will learn:
How to calculate mean, standard deviation (of sample and population), coefficient of variation, confidence interval, P-value.
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How to compare a group of samples with a mean (simple t-test), to compare two groups of samples (unpaired t-test), and group of samples before and after treatment (paired t-test)
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How to compare three or more groups (one way ANOVA), and groups of samples measured before, during and after treatment (repeated measures ANOVA)
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How to study the effect of treatment (linear regression)
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How to compare samples that are not from a Gaussian population (Wilcoxon test, Mann-Whitney test)
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How to visualize and interpret real-time PCR expression data of many genes in many samples (principal component analysis)
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How to identify related samples based on real-time PCR expression profiling (Hierarchical clustering)
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How to find response profiles describing samples studied by real-time PCR expression profiling (self-organizing maps)
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How to design real-time PCR expression studies (experimental design)
Biostatistics (2 days)
 Day 1- Statistical analysis of real-time PCR data
Lectures cover the principles of statistics, including Gaussian statistics, the central limit theorem, p values and statistical hypothesis testing, z-scores, rank-based methods (non-Gaussian), comparison of two groups (paired and unpaired t-test), Mann Whitney test, Wilcoxon rank sum test, Fisher’s exact test. Outlier detection (Dixon’s test, Grubb’s test, Cochran’s test), ANOVA and classical calibration (least square fit, correlation coefficient, Hottelings’ area). During computer based workshop participants will learn how to analyze typical real-time PCR data sets. Examples include identification of outliers, and how to compare means and variances of paired and unpaired studies.
Day 2- Gene expression profiling with real-time PCR
Lectures cover methods to classify samples and genes. The methods presented include Principal Component Analysis, Potential Curves, Hierachical Clustering, Self-Organizing Maps, and Trilinear Decomposition. During computer based workshops participants will classify metabolic genes in yeast, developmental stages in Xenopus laevis, Breast cancer data, and developing stem cells.
Biostatistics (3 days)
 Day 1- Real-time PCR experimental design and basic data processing
This day will cover experimental strategies for quantification of nucleic acids by real-time PCR, normalization and calibration of the data, and basic data analysis. We will discuss absolute calibration based on standard curves, including the effect of the sample matrix, estimation of PCR efficiency and the error in the estimation, and revere calibration to determine concentrations of test samples. We will discuss RNA and DNA based standard curves, the use of spikes, and also in situ calibration methods including serial dilution and standard additions. We will discuss the use of inter-plate calibrators and normalization with them. We will also discuss normalization with reference genes, amounts of samples, conversion of CT values to copy numbers, how to calculate relative quantities and fold changes. We will also go through methods to estimate PCR efficiencies from the QPCR response curves, and how to use the response curves for quality control. We will also learn how to identify outliers, and optimum reference genes. Computer based exercises include finding optimum reference genes using geNorm, Normfinder and PCA, absolute quantification including estimating the PCR efficiency and its confidence limits from a standard curve and determine concentrations of test samples by reverse calibration, relative quantification based on multiple reference gene, and outlier detection using the Grubb’s test.
Day 2 - Statistical analysis of real-time PCR data
We will go through the principles of statistics, including arithmetic and geometric means, standard deviation, variance, coefficient of variation, standard error, confidence interval of the mean, critical t value, Gaussian distribution, z scores, the central limit theorem, statistical hypothesis testing, one and two sided p-values, type I and type II errors, power analysis, multiple hypothesis testing, rank-based methods, resampling methods, paired and unpaired t-test, Mann Whitney test, Wilcoxon rank sum test, ANOVA, repeated measures ANOVA, F-test. During computer based workshop participants will learn how to analyze typical real-time PCR data sets. Examples include optimizing QPCR assays, paired tests, multiple hypothesis testing, comparison of methods to estimate p-values etc.
Day 3 - Gene expression profiling with real-time PCR
We will describe the latest developments in high throughput real-time PCR expression profiling, including new platforms, experimental strategies and analysis methods. These include Pearson’s and Spearman’s correlations, Principal Component Analysis, Potential Curves, Hierachical Clustering, Self-Organizing Maps, k-means, support vector machines, Trilinear Decomposition, Partial Least Squares and Neural Networks. We will also learn the concepts of mean centering and autoscaling data, which often makes normalization with reference genes unnecessary. We will also learn how to make 2-dimensional and 3-dimensional scatter plots. During computer based workshops participants will classify the expression of genes in metabolism and development, and classify samples based on differentiation state or disease.
Core module (3 days)
 Day 1:
The introductory course consists of a theoretical part and a practical part where participants get to do QPCR experiments by themselves under experienced supervision. The course contains:
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Basic PCR theory
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The theory of real-time PCR
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Applications and possibilities of QPCR. Comparison of QPCR with regular PCR.
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Review of currently available detection technologies (SYBR Green I, TaqMan, Molecular Beacons...etc)
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Different instrument plattforms and their typical uses
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Primer Design
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The problem of primer-dimer formation and how to minimize them
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Probe Design
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Experimental design and optimization
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Basic data handling and analysis
Day 2:
Building further on the topics from the previous day, apart from a brief review of the above:
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Introduction to quantification principles
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Quantification strategies, uses and limitations
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Calculations using different relative quantification methods
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Strategies for normalization of QPCR data
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In situ calibration for compensation of inhibition in samples
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Absolute Quantification
Day 3:
This course covers aspects in sample preparation and reverse transcriptions.
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Principles of RT
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Priming methods for RT
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What enzymes are preferential for different applications
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Sample Preparation (Extraction of RNA and DNA)
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Introduction to statsitics and statistical analysis of data
Immuno-qPCR module (1 day)
 This course explains the basic knowledge for protein detection and quantification through immuno-qPCR. Immuno-qPCR is an immunoassay using DNA and real-time PCR for detection and quantification of proteins. The course consists of a theoretical part and a practical part where participants get to do immuno-qPCR experiments by themselves under experienced supervision. The course contains:
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Theoretical background of Immuno-PCR
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A technology description
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How to design your own immuno-qPCR assay
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How to optimize the parameters for assay development
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How to analyze immuno-qPCR data
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A general troubleshooting for typical errors
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Application examples
RNA isolation and quality control (2 days)
 Purity and quality of your RNA samples are crucial factors that influence the accuracy and reliability of your qPCR data. Variations in RNA integrity and presence of inhibitors can completely devalue your biological conclusions. To minimize such problems, proper RNA extraction procedure and careful quality control is necessary. In this course we will take you through the entire process of RNA extraction and quality assessment. First day we will guide you through all steps from storing of tissue samples and proper homogenization approaches to different RNA isolation methods. Second day will be based on assessment of RNA quality control. You will determine total RNA concentration, check quality and test integrity of RNA samples and detect possible inhibition. More than 50 percent of the time is devoted to hands on training. Remaining time are lectures.
Sample preparation (1 day)
 One of the most important requirements to get good results from qPCR experiment is to have a template of good quality. In most cases this means having an efficient sample preparation. This course module is focused on extraction of RNA and DNA to be used as template in qPCR and reverse transcription reactions. The course covers:
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Overview of nucleic acid extraction methods
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How to properly determine the concentration of purified nucleic acids
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Extraction from limited amount of material and single cells
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Storage biological samples and purified nucleic acids
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Quality control of purified material
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Integrity of purified RNA
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How to test for the presence of inhibitors
qPCR overview (1 day)
 Molecular diagnostics and molecular research are experiencing
a technology shift. A new platform based on ultra sensitive detection of nucleic
acids called quantitative real-time PCR (qPCR) has been developed, making it
possible to determine the amounts of specific nucleic acids and even proteins in
biological samples with unsurpassed accuracy and sensitivity. This has opened
new possibilities to study and diagnose diseases based on expression patterns
and to detect pathogens in biological samples. This 1-day course will give
participants an in-depth understanding of real-time PCR technology and its
possibilities, as well as insight in the future development of the technology
platform and forthcoming applications.
Core module (2 days) Day 1:
The introductory course consists of a theoretical part and a practical
part where participants get to do QPCR experiments by themselves under
experienced supervision. The course contains:
-
Basic PCR theory
-
The theory of real-time PCR
-
Applications and possibilities of QPCR. Comparison of QPCR with regular PCR.
-
Review of currently available detection technologies (SYBR Green I, TaqMan, Molecular Beacons...etc)
-
Different instrument plattforms and their typical uses
-
Primer Design
-
The problem of primer-dimer formation and how to minimize them
-
Probe Design
-
Experimental design and optimization
-
Basic data handling and analysis
Day 2:
This course covers aspects in sample preparation and reverse transcriptions.
-
Principles of RT
-
Priming methods for RT
-
What enzymes are preferential for different applications
-
Sample Preparation (Extraction of RNA and DNA)
-
Introduction to statsitics and statistical analysis of data
To be defined
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