Schedule
- Day 1 - Concepts in Bioinformatics
- Day 2 - Transcriptomics
- Day 3 - Genetic Sequence and Structural Variation
- Day 4 - Epigenomics
- Day 5 - The Bigger Picture
Day 1 - Concepts in Bioinformatics
- Introduction
- Fundamental statistics
- Microarray technology
- Next-generation sequencing technology
- Research example: bioinformatics in cancer research
Day 2 - Transcriptomics
- Analysis of microarray data: normalization, detecting differentially expressed genes, clustering and classification
- Applications of microarray-based gene expression profiling
- Analysis of RNA-seq data: sequence alignment, read count normalization, detecting differentially expressed transcripts
- Applications of transcriptional profiling via high-throughput sequencing
Day 3 - Genetic Sequence and Structural Variation
- GWAS: SNP array genotyping & trait association
- Copy number analysis: copy number detection from SNP arrays
- Applications of copy number profiling
- Analysis of deep DNA sequencing data: variant calling, detecting structural variation
- Research example: deep sequencing in cancer research
Day 4 - Epigenomics
- Analysis of DNA methylation microarrays
- Research example: DNA methylation profiling in cancer
- High-throughput Bisulphite sequencing: visualisation of quantitative sequence data
- Immunoprecipitation and next-gen sequencing: ChIP-seq, MeDIP-seq, alignment and peak-finding
- Research example: Next-gen sequencing for cancer epigenetics
Day 5 - The Bigger Picture
- Making use of publically available data
- Functional enrichment analysis: adding interpretation to results
- Analysis of cell viability data from siRNA screens
- Functional proteomics: reverse-phase protein arrays
- Characterising metabolic profiles
- Using networks to study biological systems