Description: Several technologies, which are now entering clinical research, generate huge amounts of data requiring advanced bioinformatics and statistical tools for interpretation. One half of the course introduces methods for this including practical exercises. The other half of the course provides a general introduction to high-throughput -omics based technologies aiming at giving the participants an overview of what can be done and what are the limitations. The content in the specific areas are:
Genomics:  
- Introduction to principles and techniques behind “next generation sequencing”
- Gene panels versus whole exome sequencing for mutation screening
- Non-invasive prenatal diagnostics (whole genome sequencing, copy number variation)
- Genome-wide methylation analysis
Transcriptomics:
-Sequencing technologies overview - how to sequence DNA - from 2 samples to metagenomes
- Transcriptome analysis - measuring gene activity by sequencing
-  Basic bioinformatics for transcriptomics - challenges and pitfalls
Proteomics  
-  Introduction to clinical mass spectrometry based proteome analysis
-  Proteomics strategies in clinical proteome analysis
-  Bioinformatics - from MS data to clinical understanding of the cellular level
-  Basal quantitative studies: Protein ID, PCA and quantitative description of proteome data
Metabolomics and NMR
- Background of NMR: What is measured, what can be detected
- Metabolites and metabolomics – the place in the –omics suite
- NMR and other techniques for metabolomics
-  Applications of metabolomics
Clinical bioinformatics and statistics
- Reproducible workflows (introduction to R/Bioconductor; cluster analysis;  heatmaps)
- Basic workflows (differentially expressed features; multiple test correction; feature enrichment;
  network analysis)
- Prediction and classification (partial least squares; restricted generalized linear regression)
- Clinical trial designs for testing biomarker-based personalized therapies

Literature: Will be announced later.

Prerequisites: Masters degree; basic statistics course and knowledge of statistical software; primarily for medical PhD students without previous knowledge of the –omics techniques.

Evaluation: Attendance at lessons and participation in exercises.

Organizer: Martin Bøgsted, Professor MSO, PhD, Søren Risom Kristensen, Professor, DMSc

Lecturers: Martin Bøgsted, Professor MSO, PhD, Inge Søkilde, PhD, Suzette Sørensen, Postdoc, PhD, Kaare Lehmann, Ass. Professor, PhD, Allan Stensballe, Ass. Professor, PhD, Reinhard Wimmer, Ass. Professor, PhD, Steffen Falgreen, Postdoc.

ECTS: 3.2

Time: 20-23 October, 2014

Place: Forskningens Hus, Aalborg Universitetshospital

Zip code:
9000

City: Aalborg

Number of seats:

Deadline: 29 September, 2014