Applied bioinformatics 1400-126BP

A short theoretical introduction will precede each class, but most of the time will be devoted to independent work and problem solving under the tutors' supervision.

The topics discussed during the classes will include:

1. Introduction to programming: bash and R.
2. Introduction to next-generation sequencing (NGS) data processing: introduction to the basics of sequencing methodology and Illumina data handling, fastq format, raw data quality analysis, preparation of data for assembly and further analysis, genomes and transcriptomes assembly, assembly quality analysis, coverage assessment (bam and sam formats), contamination and completeness estimation.
3. Genome analysis. Whole-genome analysis: whole-genome alignment, detection of large rearrangements. Basic annotation methods: homology-based gene prediction and functional annotation (bed and gff data formats). Basic categories describing the characteristics and functions of genes and proteins (e.g. GO, COG, KEGG categories, EC numbers). Visualization of genomic data.
4. Introduction to transcriptome analysis, processing of raw RNA-seq data from the Illumina platform, visualization and detection of differences in gene expression, preliminary analysis of the obtained data.
5. Introduction to phylogenetics and molecular modelling, sequence alignment, protein structures modelling and phylogenetic trees reconstruction based on sequence and structural data.
6. Introduction to amplicon analysis and metagenomics.
NOTE: each topic will be covered in more than one class.