mybiogazelle

1. experiment design

power analysis, experiment layout (sample vs gene maximization), biological and technical replicates, inter-run calibration

2. sample preparation and quality control

pre-amplification, DNase treatment, cDNA synthesis, RNA integrity and purity

3. assay design and quality control

RTprimerDB assay database and primer design, probes vs intercalating dye, design guidelines, in silico evaluation (specificity, splice variants, secondary structures, SNPs), empirical validation (melt curve, electrophoresis, standard curves)

4. qPCR analysis [course notes here]

real-time PCR principle, amplification curve, melt curve, Cq value determination methods, replicates & controls, speed and throughput considerations

quantification models (delta-delta-Cq, Pfaffl, qbasePLUS), efficiency correction, inter-run calibration, result rescaling

5. normalization

normalization with multiple reference genes, selection and validation of reference genes (geNorm), alternative normalization methods (global mean, expressed repeats)

6. quality control on post-PCR data

melting curve analysis, PCR efficiency, replicates, reference gene stability, negative/positive controls, normalization factors, QC on inter-run calibration

7. bio-statistical analysis

basic principles, descriptive statistics, selection and application of appropriate statistical tests

8. reporting guidelines

MIQE, RDML

Various chapters are accompanied with interactive and hands-on computer exercises in qbase^PLUS