Bioinformatics and Genomics

This repository contains information about the Module D1/G1 - Bioinformatics and Genomics of the Biology Master curriculum at the University of Graz.

Contents

This module is part of the specialization in “Evolutionary Ecology” and the specialization in “Digital Biology.” The focus of this module is on essential skills for producing as well as evaluating, organizing, and analyzing large biological datasets, with special attention, but not limited to, molecular biology data. Among others, the following topics will be covered:

  • Current technologies, methods, and databases in the field of DNA/RNA sequencing

  • Fundamental algorithms in computer-assisted molecular biology

  • Modern computer-assisted tools, applications, and computing infrastructure for large-scale analyses of DNA/RNA and other data

  • Reproducibility in modern computer-assisted biology and data science in general

The module is devided into 3 individual lectures:

  1. Genomic Methods in Evolutionary Biology and Ecology

  2. Databases in Ecology and Comparative Genomics

  3. Fundamentals of Reproducable Data Analysis

Expected Learning Outcomes and Competencies

Upon completion of the module, students will be able to:

  • Design evolutionary biological and ecological studies based on DNA/RNA data

  • Select appropriate sequencing technologies and applications for studies

  • Evaluate high-throughput data (NGS) of various types (QC)

  • Analyze high-throughput data (NGS) both qualitatively and quantitatively

  • Explain and apply fundamental algorithms of computer-assisted molecular biology

  • Interact with important public biological databases

  • Use High Performance Computing infrastructure (HPC)

  • Process large (biological) datasets efficiently and reproducibly

  • Organize large (biological) datasets and utilize workflow management systems

  • Use and develop software containers and computer-assisted automated workflows

Teaching and Learning Activities, Methods

Lectures by teachers and students, a mix of interactive didactic teaching and guided practical work and exercises, independent work in small groups, writing of written assignments

Syllabus

Genomic Methods in Ecology and Evolutionary Biology

Day

Topics

1

Introduction to Linux, working on the command line, working on remote computers.

2

Working with HTS data, evaluation of data quality, data filtering

3

Genome assembly, evaluation, Metagenome cleaning

4

Transcriptome assembly, differential gene expression analysis

5

Genome annotation, Orthology, Phylogenomics

6

Working on individual project

7

Working on individual project

8

Working on individual project

Databases in Ecology and Comparative Genomics

Day

Topics

1

Sequence Databases and similarity search

2

Metabarcoding databases: taxonomic assignment and ecological metadata

3

Databases for functional annotation

4

Working on indiviual projects

Fundamentals of Reproducible Data Analysis

Day

Topics

Material

1

Advanced command line, random numbers, Reproducible software installation, Data organication, Git

about

working environment

exercise 1

exercise 2

exercise 3

exercise 4

2

Virtual environments, Container basics, advanced topics and pitfalls

exercise 1

exercise 2

exercise 3

exercise 4

3

Workflow management systems: GNU Make, Snakemake, Nextflow

exercise 1

4

Working on individual project

exercise 1