Genome-scale technologies

obligatory courses

Learning modern methods (experimental and bioinformatic) of high-throughput genomics data generation and analysis on the level of the genome, transcriptome and proteome.

1. Introduction - traditional sequencing methods for DNA (Sanger), RNA (EST and microarrays) and peptides (Edman degradation).

Lab: intro to galaxy

2. Next generation DNA sequencing methods, library preparation and quality control.

Lab: NGS quality control, filtering and trimming reads

3. Mapping NGS reads to genomes

Lab: read mapping in practice

4. DNA methylation sequencing

Lab: Maping reads from bisulfite-seq, calling methylated sites

5. RNA sequencing

Lab: read counting for genes and transcripts, differential gene expression

6. Histone modifications and ChIP-Seq

Lab: identification of enriched regions in ChIP-Seq data

7. DNA Variant identification from NGS

Lab: SNP detection in NGS data

8. Metagenomics

Lab: metagenomic read assignment to phylogenetic clades

9. Qualitative proteomics, mass spectrometry

Lab: peptide identification in MSMS spectra

10. Quantitative proteomics

Lab. differential MS spectra analysis

11. Gene networks (genetic, PPI, coexpression, etc), functional annotation

Lab. Network visualization and ontology annotations

12. Test

Lab. Project work

13. Sequence assembly based on NGS reads

Lab. Project work

14. Single cell omics techniques

Lab. Single cell RNA-Seq analysis with Seurat

Next-generation Sequencing: Current Technologies and Applications Jianping Xu (Editor)

Bioinformatics and Functional Genomics 3rd edition Jonathan Pevsner

Obtaining the ability to analyse data originating from high-throughput technologies and inference of biologically meaningful results from these data

Written test (50%) + project (50%) -> exam admission threshold is 60%

Oral exam.