ECTS credits:
5

Course parameters:
Language: English
Level of course: PhD course
Semester/quarter: Q4, 28 June - 2 July, 2021, one week course
Hours per week: 35
Capacity limits: 40

Objectives of the course:
At the end of the course the students should have a detailed knowledge of bioinformatics methods for genome analysis using next-generation sequencing data. This includes knowledge of the existing types of sequencing data, how the different types of data can be displayed and analysed, the current methods for genome assembly and analysis, their accuracy, and how to apply them. The course will train the participants to devise and analyse a real genomics project involving NGS data.

Learning outcomes and competences:

At the end of the course the student should be able to:

• Describe key challenges in analysis of NGS data.
• Explain the theoretical foundation of methods using NGS for assembling and analysing genomes.
• Discuss the bioinformatic methods for genome analysis.
• Discuss original literature within the subjects.
• Use bioinformatics tools within the selected application areas.

Compulsory programme:
Course participation and submission of a data analysis report.

Course contents:
The course will start with an overview of current NGS technologies and directions in which these are currently progressing. Methods for assembling genomes from NGS data using either a reference genome or de novo assembly will be presented together with some emphasis on assessing NGS data quality (Quality control, accuracy of base calling). The course will then offer an overview of the range of biological/biomedical questions that these new types of data can help to address. This includes:

How to build a Bioinformatics pipeline:

• The use of NGS resequencing of closely related genomes for detecting mutations. This includes the characterization of somatic mutations in cancer tissues, the de novo mutation spectrum in eukaryotic genomes, and the detection of mutations underlying phenotypic changes in experimental or natural populations.
• Short-read (Illumina) versus long-read (Pacbio, Nanopore) sequencing
• The use of resequencing of a large number of individuals for Single Nucleotide Polymorphism (SNPs) and Copy number variation detection.
• Application of NGS in Transcriptomics and Epigenomics.
• Single-cell RNA-seq studies that go beyond tissue-type analysis to resolve single cell behavior
• Environmental/Meta-genomics studies probing the bacterial/viral diversity of understudied biomes.
• Comparative and evolutionary genomics.

To allow hands-on data analysis training, the course includes the following computer exercises, which can be completed using either your own or example data:

• Introduction to Galaxy, GATK and Samtools
• Grooming of reads
• Mapping of Illumina reads to reference
• SNP/indel calling, filtering and annotation
• Gene models and transcript quantification
• De novo assembly of bacterial plasmids using short and long NGS reads
• Analysis of single-cell RNA-seq data

Prerequisites:
3 years study of molecular biology, biology, mathematics, engeneering or computer science.

Name of lecturer[s]:
Mikkel Schierup and Stig Uggerhøj Andersen

Type of course/teaching methods:
One week intensive course including lectures, colloquia and computer exercises.

Literature:
Review and research articles.

Course homepage:

https://international.au.dk/education/admissions/summeruniversity/courses/next-generation-sequencing/

Course assessment:
Individual written report

Provider:
Bioinformatics Research Center (BiRC)

Special comments on this course:
None

Time:

28 June – 2 July 2021

Place:
Bioinformatics Research Center, Aarhus University, Building 1110 or online via Zoom

Registration:
Deadline for registration is 20 May, 2021. 

For registration: sign up through AU Summer University (https://international.au.dk/education/admissions/summeruniversity/courses/next-generation-sequencing/

) or contact the teachers by e-mail - sua@mbg.au.dk or mheide@cs.au.dk 

If you have any questions, please contact Stig Uggerhøj Andersen (sua@mbg.au.dk) or Mikkel Schierup (mheide@cs.au.dk).