Course - Bioinformatics Methods for next Generation Sequencing Analysis - MOL8008
Bioinformatics Methods for next Generation Sequencing Analysis
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About the course
Course content
The course will introduce bioinformatic approaches, tools and pipelines for computational analyses of Next Generation Sequencing (NGS) data. Focus will be on analysis methods for coding and non-coding RNA from RNA-seq, and transcription factors and epigenetic markers from ChIP-Seq. The course will cover strategies, methods and workflows used for analyses of such data, including mapping to reference genomes, feature extraction, and statistical analysis. In addition, the biological interpretation of output from such analyses will be presented as case studies from scientific journals.
Learning outcome
Knowledge
- Explain the basic mechanisms of transcription, gene regulation and miRNA regulation
- Describe the concept behind Next Generation sequencing methods for RNA-Seq, ChIP-Seq and miRNA-Seq
- Describe the basic bioinformatics workflows for RNA-Seq (including isoform analysis), ChIP-Seq and miRNA-Seq
Skills
- Setup and run a NGS processing pipeline for analysis of sequencing data
- Interpretate results from NGS analysis using basics statistics and standard online bioinformatics tools
- Present setup and results from an NGS data analysis project in form of a Scientific Paper
Competence
- Recognise what types of research questions that can addressed by NGS analysis
- Assist in design and implementation of an NGS experiment in the participants own workplace or research facility.
- Conduct and explain analysis of NGS data from a hypothesis driven standpoint and an explorative standpoint
Learning methods and activities
There will be a one week intensive period of lecturing, followed by a period of self-study and project work. The exam will be on a pass/fail basis based on the evaluation of their project work.
Compulsory assignments
- Attendance in lectures
Further on evaluation
Attendance of at least 80% of the lectures is mandatory in order to take the exam.
Retake of exam: If the student has participated in the intensive course week with lectures and exercises, the student can submit a new project report for assessment the following year without participating in the intensive course week.
Recommended previous knowledge
Attending students should be familiar with basic high-level programming of scripting languages like Python, R and Matlab. Some basic knowledge in applied bioinformatics is recommended.
Required previous knowledge
Masters degree in relevant programmes. Medical Doctors degree. Or medical students at The Student Research Programme. Candidates with other or lower degree will be assessed individually.
Course materials
Scientific publications. Handouts of presentations.
Subject areas
- Molecular Medicine
- Medical Technology
- Bioinformatics