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TATAA Biocenter qPCR Training Course – Biostatistics
This course is being held in conjunction with the Advances in qPCR conference.
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. This course is based on seminars and computer-based demonstrations.
Learning Objectives
- 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)
Topics and Course Organization
- Basic principles of statistics
- Advanced principles of statistics
- Overview of statistical tests
- Statistical testing for significant differences
- Pattern recognition and Hierarchical Clustering
- Scatter plot, Principal Component Analysis, Potential Curves, Procrustes Rotation
- Gene expression profiling
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