Learning objectives
Knowledge and understanding: learning the principles of Next-Generation Sequencing data analysis.
Ability to apply knowledge and understanding: Students will acquire the basic skills necessary to perform bioinformatics analysis related to the understanding of gene expression and molecular mechanisms starting from NGS data
Prerequisites
Knowledge of regulatory mechanisms of Eukaryotic organisms.
Basic computer usage relative to data repository access and data download. Preferred, but not required: basic knowledge of UNIX or other programming language.
Course unit content
General notions of Next-Generation sequencing (NGS).
Choice of the appropriate NGS experiment.
Tools for the analysis of NGS experiments.
NGS data format and consequent tools for manipulation and display.
NGS analysis through GalaxyProject platform (GUI, web browser): Quality Control (QC), alignments, alignment analysis, alignment visualization.
Data analysis of ChIP-seq, RNA-seq, DNA methylation, and chromatin accessibility (ATAC-seq).
Formatting of NGS data for genome browser visualization.
Secondary analytical tools for the analysis of specific genomic regions as promoters or regulatory regions.
Integration of NGS data.
Generation of figures (paper-ready).
Full programme
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Bibliography
Selected scientific articles
Teaching methods
The course consists of lectures on the main topics covered by the program, and targeted in-depth analysis of topics of particular relevance and interest, also with the help of recently published NGS datasets.
Assessment methods and criteria
The assessment of the expected learning outcomes is based on an oral exam and a practical exercise on the topics covered.
The student must be able to apply one of the methods taught in the course to assigned datasets.
Both the theoretical knowledge and the ability to apply that knowledge to solve experimental problems
Other information
A personal laptop is required.
2030 agenda goals for sustainable development
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