Duration
10h Th, 90h Mon. WS
Number of credits
| Master in bio-informatics and modelling, research focus | 10 crédits |
Lecturer
Denis Baurain, Luc Cornet, Tom Druet, Frédéric Farnir, Marc Hanikenne, Alexandre Hego, Arnaud Lavergne, Sébastien Massart, Pierre Tocquin, Kristel Van Steen
Coordinator
Language(s) of instruction
English language
Organisation and examination
Teaching in the second semester
Schedule
Units courses prerequisite and corequisite
Prerequisite or corequisite units are presented within each program
Learning unit contents
Partim Introduction and RNA-Seq analysis
High-throughput sequencing technologies generate large volumes of data whose analysis requires the use of bioinformatics tools, command-line environments and, for some analyses, high-performance computing (HPC) resources.
This partim consists of several modules:
- Module 1. Introduction, sequence QC and filtering
- Module 2. Introduction to high-performance computing (HPC)
- Module 3. RNA-Seq data analysis
Partim scRNA-Seq
4 half-days:
- 1 theoretical session - Theoretical concepts of single-cell analysis
- 3 practical sessions
- Introduction to the Seurat pipeline
- Integration and multi-assay analysis
- Individual work on a single-cell analysis
Partim AI-based image analysis
This partim aims to put into practice the concepts of advanced biological and biomedical image analysis using artificial intelligence introduced in the BIOC0727-1 and INFO0965-1 courses.
It allows students to become familiar with good practices and image analysis methodologies adapted to a specific thematic and experimental context.
Indicative programme
- Case study 1: group work focused on designing an image analysis workflow. Students present the proposed strategy, its advantages, limitations and the required quality controls.
- Case study 2: individual critical analysis of a workflow or provided results. The student must identify methodological choices, possible biases, limits of interpretation and required validation steps.
This partim presents different applications of quantitative genetics and genomics to the study of domestic or wild animal populations. Developments in genotyping and genome resequencing technologies now make it possible to address a wide range of questions in population genetics and quantitative genetics.
The proposed applications are mainly based on molecular markers and genotype data. Each session begins with an introduction to the relevant concepts, followed by their practical application using quantitative or population genetics software. Topics covered include:
- Presentation of data formats and use of software (data filtering, format conversion, calculation of basic statistics, etc.);
- Estimation of relatedness using molecular markers;
- Inbreeding and runs of homozygosity, and their relationship with the demographic history or diversity of populations;
- Haplotype phasing and imputation of missing genotypes.
Partim Microbiota analysis
With the exponential growth in the amount of data generated in the life sciences, bioinformatics now plays a central role in research and development, including in agronomy.
The aim of this course is to develop students' analytical skills, their ability to select and apply algorithms relevant to a scientific question, and their ability to explain the operations performed and the results obtained to biologists who are not bioinformaticians. In short, the main objective is to learn how to translate expressed needs and scientific questions into the most appropriate computational analyses.
This course is based on project- and action-based learning. Starting from a scientific problem and high-throughput sequencing data, students will set up and use a data-analysis pipeline. The scientific question will involve comparing the microbial communities present in different samples.
After a theoretical introduction and presentation of the project context, students will receive high-throughput sequencing data from microbial communities together with the objective of the analysis.
The course is organised around the development of a project and focuses on the selection, application and documentation of a bioinformatics pipeline using the QIIME software suite. Video tutorials will be available to guide students, and meetings with the teaching team will provide support throughout the process.
Partim Reproducible metagenomic analysis with Nextflow and Singularity/Apptainer
This case study allows students to put into practice the skills acquired in bioinformatics workflows, containerisation and reproducibility through the complete analysis of a metagenomic dataset in an HPC environment.
Starting from metagenomic sequencing data, students will carry out the main steps of an analysis aimed at reconstructing and identifying the genomes present in the sample: metagenome assembly, binning of contigs to reconstruct individual genomes (MAGs), assessment of genome quality and taxonomic identification. When taxonomic identification needs to be refined, students will complement the analysis with 16S rRNA analysis. Selected sequences will then be incorporated into a phylogenetic analysis to refine their taxonomic placement.
All analyses will be performed on the NIC5 computing cluster using GEN-ERA workflows based on Nextflow and Singularity/Apptainer.
Partim Network-type approaches for Precision Health
This partim will emphasize network-type approaches (hence systems views), including sample-specific networks. These networks are constructed for every sample separately (for instance, a taxa, or a patient) and allow clustering taxa/patients or predicting with them, all within Precision Health (One Health). The construction of these networks would focus on reverse-engineering from a (more classical) population network.
Learning outcomes of the learning unit
Partim Introduction and RNA-Seq analysis
At the end of the course, students will have acquired basic practical knowledge for the analysis of high-throughput sequencing data. The course involves extensive use of the command line, interaction with a computing cluster and implementation of commonly used analysis pipelines.
Partim scRNA-Seq
At the end of this partim, students will be able to understand the main concepts related to single-cell transcriptomics data and to perform and interpret a basic scRNA-Seq analysis.
Partim AI-based image analysis
At the end of the course, students should be able to define and implement a complete image analysis workflow adapted to the nature of the images and to the experimental context, in order to address a research question. They should demonstrate their ability to use the different tools introduced in the BIOC0727-1 and INFO0965-1 courses.
Partim Applications in quantitative genetics and genomics
This partim aims to prepare students to understand different concepts in quantitative and population genetics used to study or manage animal populations. Students will also develop an understanding of the associated modelling and programming concepts. They should be able to identify an appropriate analysis, install software and execute the relevant commands using instructions or user manuals. Students should also be able to interpret the results and explain them.
Partim Microbiota analysis
The learning outcomes are as follows:
- Ability to set up a bioinformatics analysis pipeline for high-throughput sequencing data according to the biological questions being addressed, i.e. to translate a biological question into a bioinformatics analysis using appropriate tools;
- Ability to critically evaluate a bioinformatics pipeline;
- Ability to extract biologically relevant information from raw data;
- Ability to interpret large datasets qualitatively and quantitatively.
At the end of the partim, students will be able to implement, document and interpret a reproducible metagenomic analysis workflow in an HPC environment, using workflow-management and containerisation tools.
Partim Network-type approaches for Precision Health
Prerequisite knowledge and skills
This course builds on the learning outcomes of BIOC0726-1, BIOC0727-1, INFO0964-1, INFO0962-1 and INFO0965-1.
For the partim Applications in quantitative genetics and genomics, basic knowledge of genetics is required. Students should also master the basics of R for statistical analysis and graphical representation of results, as well as the use of Linux from the command line. Basic programming skills are required for the implementation of some analyses.
Planned learning activities and teaching methods
Partim Introduction and RNA-Seq analysis
Each module begins with a brief theoretical introduction, followed by hands-on computer-based work in a computer room.
Partim scRNA-Seq
In addition to the theoretical introduction, the practical sessions consist of hands-on computer-based analyses.
Partim AI-based image analysis
The case studies will be introduced through an in-person theoretical session.
The first case study will consist of group work, partly carried out during class but also requiring work outside the classroom. This case study will be assessed in class during the second session.
The second case study will consist of individual work, leading to a written report and assessed during the examination session.
Partim Applications in quantitative genetics and genomics
Each session begins with an introduction to the relevant concepts (approximately one hour). Datasets are then provided for computer-based exercises, together with an instruction sheet describing the objectives to be achieved (a tutorial). In several sessions, students will be asked to program a method. Instructions will first be presented in person, and the results of the analyses will be discussed during the following session.
Partim Microbiota analysis
The course follows a flipped-classroom and learning-by-doing approach. A general lecture will introduce the context, objectives, learning methods and assessment procedures.
The raw data to be analysed will also be provided to the students.
Online tutorials will then be made available. These tutorials explain how to set up the bioinformatics analysis pipeline and the purpose of the different analyses that can be performed. Students will have to select the most relevant analyses.
Based on these tutorials and their own research, students will develop a bioinformatics analysis pipeline enabling them to interpret the raw data provided. Throughout the development process, students will be coached by the teacher through regular meetings to review progress, guide further development and resolve problems.
Pipeline development is individual, but students are also encouraged to collaborate with one another through peer learning.
Partim Reproducible metagenomic analysis with Nextflow and Singularity/Apptainer
The course will begin with a theoretical session presenting the dataset and analysis strategy, together with a demonstration of the main tools and workflows used.
Students will then work independently in guided practical sessions. They will be expected to consult and use the official documentation to determine the commands, parameters and steps required to complete the analysis.
Students will progressively document their work in a laboratory notebook.
Partim Network-type approaches for Precision Health
Activities will couple theory with working on a project, either alone or in groups
Mode of delivery (face to face, distance learning, hybrid learning)
Face-to-face course
Further information:
This course is taught in person; attendance at the sessions is mandatory. However, its problem-based approach will require individual work outside the classroom for each partim.
Course materials and recommended or required readings
Platform(s) used for course materials:
- eCampus
Further information:
Platform used for course materials:
eCampus
Introductory tutorial for the Microbiota analysis partim: https://www.youtube.com/watch?v=6564K4-_DBI
Exam(s) in session
Any session
- In-person
written exam AND oral exam
Written work / report
Continuous assessment
Further information:
General principle:
The final grade for the course will be calculated as a weighted average of the grades obtained for each partim. A grade of at least 7/20 in each partim and a weighted average of at least 10/20 are required to pass the course. For the second examination session, a partial exemption is granted for partims in which a grade of at least 10/20 was obtained in the first session. Partial exemptions cannot be carried over from one academic year to the next.
The following assessment methods apply to the different partims:
Partim Introduction and RNA-Seq analysis
Assessment is based on a final oral examination, complemented by continuous assessment based on participation during the course sessions.
Weighting:
- 20% Active participation during the sessions
- 20% Written report (RNA-Seq analysis)
- 60% Oral examination
Assessment includes:
- A written report (20%)
- A written examination on the theoretical component (30%)
- An oral presentation of the student's analysis (50%)
Assessment is based on a final oral examination, complemented by continuous assessment based on participation during the two course sessions.
Weighting:
- 20% Active participation during the sessions
- 20% Written report for case study 2
- 60% Oral examination
This partim will be assessed through an oral examination worth 14 points. During the examination, students must be able to explain the concepts covered in the course, interpret the results, and understand and explain the methods, algorithms and code used. Questions will also be based on the reports submitted. An additional 6 points will be awarded for three programs designed to perform specific tasks (2 points per program). Instructions will be provided at the end of the session; the programs must be submitted on time, and students must be able to explain both the code and how it works.
Attendance at in-person sessions is mandatory. Each unjustified absence will result in a deduction of 1 point from the examination grade per missed session. After each session, students must submit a report. If a report is not submitted on time or is considered insufficient, 2 points will be deducted from the final grade for each report concerned.
Partim Microbiota analysis
Assessment will be based on the results of the project.
More specifically, the grade will be the average of the documentation of the implemented pipeline (bioinformatics documentation component) and the analysis report, which should translate the bioinformatics analysis results into information that can be used by a biologist.
A PDF document of no more than 5 pages must be submitted for the documentation component, and the results will be presented in a PowerPoint presentation of no more than 6 slides.
The second component will be assessed through an oral examination.
Partim Reproducible metagenomic analysis with Nextflow and Singularity/Apptainer
Assessment will take the form of an oral presentation of the laboratory notebook produced during the case study.
Partim Network-type approaches for Precision Health
Students will need to submit a written report (50% of the note), then defend it orally at the exam (50%).
Work placement(s)
Organisational remarks and main changes to the course
Each M-BIM student must bring a laptop on which a Linux operating system (such as Ubuntu LTS) can be installed. Interactive virtual machines in VirtualBox are not a reliable solution, but WSL2 on a recent Windows system is an option, as is dual boot with Windows.
A recent Apple Mac can also be used.
Each student must also bring a laptop on which QuPath and Fiji/ImageJ can be installed and run.
Contacts
Responsible teacher(s):
Course coordinator: Marc Hanikenne
E-mail address: marc.hanikenne@uliege.be
Partim Introduction and RNA-Seq analysis
Marc Hanikenne
E-mail address: marc.hanikenne@uliege.be
Partim scRNA-Seq
Arnaud Lavergne
E-mail address: arnaud.lavergne@uliege.be
Partim AI-based image analysis
Pierre Tocquin, Alexandre Hego
E-mail addresses: ptocquin@uliege.be, alexandre.hego@uliege.be
Partim Applications in quantitative genetics and genomics
Tom Druet, Frédéric Farnir
E-mail addresses: tom.druet@uliege.be, f.farnir@uliege.be
Partim Microbiota analysis
Sébastien Massart
E-mail address: sebastien.massart@uliege.be
Partim Reproducible metagenomic analysis with Nextflow and Singularity/Apptainer
Luc Cornet, Denis Baurain
E-mail addresses: luc.cornet@uliege.be, denis.baurain@uliege.be
Partim Network-type approaches for Precision Health
Kristel Van Steen
E-mail address: kristel.vansteen@uliege.be