Day 1:
This 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, hydrolysis probes, Molecular Beacons...etc)
Different instrument platforms 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:
Introduction to quantification principles
Quantification strategies, uses and limitations
Calculations using different relative quantification methods
Strategies for normalization of qPCR data
In situ calibration for compensation of inhibition in samples
Absolute quantification
Day 3:
Sample Preparation (Extraction of RNA and DNA)
Principles of RT
Priming methods for RT
RT optimization
The MIQE guidelines
Group discussion, bring your own questions
2 days hands-on qPCR
Day 1:
This 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, hydrolysis probes, Molecular Beacons...etc)
Different instrument platforms 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:
Introduction to quantification principles
Quantification strategies, uses and limitations
Calculations using different relative quantification methods
Strategies for normalization of qPCR data
In situ calibration for compensation of inhibition in samples
Absolute quantification
3 days Experimental design and statistical data analysis for qPCR
This is a comprehensive course teaching the basics of statistics including the most common methods to analyze univariate as well as multivariate qPCR. The course includes extensive computer based exercises.
Day 1- Real-time PCR experimental design and basic data processing
Basic Principles of statistics, Descriptive statistics (arithmetic and geometric mean, standard deviation, coefficient of variation, standard error, confidence interval)
Experimental design (two groups with and without control, repeated measures design, trend studies, nested designs)
Absolute quantification, standard curve, runs test, outlier test, reverse calibration, limit of detection
• Exercise
Day 2 - Statistical analysis of real-time PCR data
Advanced principles of statistics, Gaussian distribution, z-score, central limit theorem, null hypothesis, p-value,
Univariate vs multivariate/multiway data, hierarchical clustering, Dendrograms, distance measures, cluster distances, missing data, mean centering, autoscaling, heat map
Reference genes, geNorm, Normfinder, accumulated SD, reference genes or total RNA
Multi marker classification, Principal Component Analysis, Potential cures, Self Organized Map, matrix augmentation, trilinear decomposition
Artificial neural network, classification vs. calibration, Partial Least Squares (PLS)
Exercises
2 days Experimental design and statistical data analysis for qPCR
The two-days course covers the most of the same prinicples as the three-day analysis course but less comprehensive and with less practical excercises
Day 1- Statistical analysis of real-time PCR data
Basic principles of statistics
Advanced principles of statistics
Statistical tests
Ability to detect a difference
Day 2- Gene expression profiling with real-time PCR
Multiplate measurements
Standard curves and absolute quantification
Experimental design, Selecting reference genes
Relative quantification, Comparison of groups
Expression profiling
1 day Biostatistics
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. The 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.
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)
How to compare three or more groups (one way ANOVA), and groups of samples measured before, during and after treatment (repeated measures ANOVA)
How to study the effect of treatment (linear regression)
How to compare samples that are not from a Gaussian population (Wilcoxon test, Mann-Whitney test)
How to visualize and interpret real-time PCR expression data of many genes in many samples (principal component analysis)
How to identify related samples based on real-time PCR expression profiling (Hierarchical clustering)
How to find response profiles describing samples studied by real-time PCR expression profiling (self-organizing maps)
How to design real-time PCR expression studies (experimental design)
1 day Advanced biostatistics
To take full advantage of the great sensitivity and high accuracy of qPCR it is important to design the experiments properly including using proper controls and standards, and then evaluate the data adequately to separate the biological information from the experimental noise and inter subject variation. This course teaches how to get the most out of qPCR measurements in terms of biological information. It is targeting qPCR users that already knows the basics of qPCR and are also familiar with the basics of statistics. The course covers:
Introduction to qPCR theory, DCq and DDCq
Absolute quantification, qPCR standard curve, Reverse calibration, Limit of detection
Experimental design, Noise contributions to RT-qPCR analysis (nested ANOVA), cost-performance optimization of experiments
Relative quantification, qPCR data pre-processing, Outlier detection. Comparison of groups (parametric and non-parametric methods)
Expression profiling, missing data treatment, scaling of data, Un-supervised clustering of genes and samples (hierarchical clustering, self-organized maps, Principal Component Analysis), Supervised clustering of samples (Artificial neural network)
Exercises
2 days Sample preparation and quality control of nucleic acids
One of the most important requirements to get good results from qPCR experiments 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. It also includes the important quality control steps needed to asure reliable results. The course covers:
Overview of nucleic acid extraction methods
How to properly determine the concentration of purified nucleic acids
RNA extraction from blood
Extraction from limited amount of material and single cells
Storage of biological samples and purified nucleic acids
Quality control of purified material
Integrity of purified RNA
How to test for the presence of inhibitors
Troubleshooting
1 day Sample preparation
One of the most important requirements to get good results from qPCR
experiments 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. It also includes the important quality
control steps needed to asure reliable results. The course covers:
Overview of nucleic acid extraction methods
How to properly determine the concentration of purified nucleic acids
Storage of biological samples and purified nucleic acids
Quality control of purified material
Integrity of purified RNA
How to test for the presence of inhibitors.
2 days Expression profiling
Day 1 Experimental design
Lectures cover the design of large expression profiling experiments, including plate design and interplate calibration. Lectures also cover the pre-processing of gene expression profiling data. Hands-on experiments include expression profiling of developing Xenopus laevis (African claw frog). Experiments are performed on conventional 96/384 well plate instruments and also on the BioMark microfluidic platform.
Day 2 Analysis of gene expression profiling data
Lectures cover methods to classify samples and genes based on unsupervised and supervised methods. Unsupervised methods include Principal Component Analysis, Potential Curves, Hierarchical Clustering and Self-Organizing Maps. Also supervised methods are presented in the form of artificial neural networks. Collected data from the previous day are analyzed in hands-on workshops supervised by expert instructors.
1 day Immuno-qPCR
This course shows how real-time PCR can be used to quantify proteins. The course consists of a theoretical part which explains what immuno-qPCR is and how it can be set up and used. The course also includes a practical part where the course participants will run an immuno-qPCR experiment to quantify a protein. The course covers:
Introduction to immunoassays
A technology description
How to set up an immuno-qPCR assay
How to optimize an immuno-qPCR
How to analyse immuno-qPCR data
Troubleshooting
Examples of immuno-qPCR applications
Practical experiment quantifying a protein
1 day Multiplex PCR
This is a 1-day course in multiplex PCR with a focus on multiplex real-time PCR. The course consists of a theoretical part and a practical part where participants get to do multiplex qPCR experiments by themselves under experienced supervision. The course contains:
Introduction to multiplex PCR
Multiplex PCR applications
Primer design
Instrument, filter set and dye considerations
Optimization of multiplex assays
Validation of multiplex assays
1 day HRM
This is an introductory course in HRM, where a high resolved melting curve is used to analyze very small differences in melting temperature of PCR products, differences that can be due to a single base substitution. The course includes seminars as well as hands-on training where the participants get to perform experiments. The course covers:
