=========================== 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, | `about `_ | | | Data organication, Git | | | | | `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 `_ | +-----+------------------------------------------------------------------------------+------------------------------------------------------------------------------------------------------+ .. toctree:: :caption: Linux Intro :maxdepth: 2 :hidden: :glob: linux-intro/README.md .. toctree:: :caption: Course materials :maxdepth: 1 :hidden: :glob: AMEB_HPC_demo/README short-read-processing-and-assembly/README post-assembly-intro/README phylogenomics_intro_vertebrata/README.md sequence_databases_similarity_search/README.md metab_db/README.md functional_annotation_db/README.md reproducibility-workshop/introduction/about.rst reproducibility-workshop/introduction/setup.rst reproducibility-workshop/day-1/exercise-1-shell-intro.rst reproducibility-workshop/day-1/exercise-2-reproducible-software-installation.rst reproducibility-workshop/day-1/exercise-3-data-organization.rst reproducibility-workshop/day-1/exercise-4-git.rst reproducibility-workshop/day-2/exercise-1-conda.rst reproducibility-workshop/day-2/exercise-2-docker-intro.rst reproducibility-workshop/day-2/exercise-3-advanced-docker.rst reproducibility-workshop/day-2/exercise-4-docker-pitfalls.rst reproducibility-workshop/day-3/exercise-1-workflows.rst reproducibility-workshop/day-3/exercise-2-phylogenomics.rst