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Molecular Data Science: from disease mechanisms to personalized medicine

Focus of the course: Molecular Epidemiology in Ageing research

Biomedical research increasingly involves the generation and analysis of very large data sets whether it is whole-genome DNA sequencing, gene expression, or magnetic resonance imaging data. In particular, large-scale data will be the cornerstone of personalized medicine. This course is aimed at biomedical students who not only want to be responsible for the generation of large-scale data in their future projects, but also want to be able to analyse and interpret their own data.

Literature and documents for study assignments will be handed out during the course.

Coordinators

Bas Heijmans, Molecular Epidemiology; 071-526 69785, [email protected]

Ingrid Meulenbelt, Molecular Epidemiology; 071-526 9734, [email protected]

Location

Leiden University Medical Center, Albinusdreef 2, 2333 ZA Leiden: Room J1-84 at the main building. For the practicals, computers in J1-84 will be used.

Storing valuables

Store valuables, especially during breaks, in one of the lockers available for library users, located on the left of the library entrance.

Assessment plan

  • Handing in assignments (Pass/Fail, individually assessed).
  • Contribute to interim evaluation of student participation and development during workgroups (0%).
  • Fill out project proposal form as preparation for reflective assignment (0%).
  • Presentation project proposal (background, hypothesis, pilot data, objectives, study design, workplan, expected outcomes; 45%, assessed in duos).
  • Active and critical participation during discussion after project presentations of peers (15%, individually assessed).
  • Reflective assignment that shows mastering key aspects of development of research proposal in molecular data science and addressing points raised during peer review (40%, individually assessed).

Overall the evaluation will be a score between 0-10 composed of a weighted average of the different modules.

Part 1: Acquiring Knowledge and Skills

Students will gain knowledge of the different study designs used in investigations, with a focus on complex diseases. In the practicals, students will acquire skills (bioinformatic and statistical tools) that will enable them to analyse large datasets of genetic, gene expression, and phenotypic data, to identify patterns in this data, and match results with existing biological information to form new hypotheses.

Week 1

Monday October 21 (Location J1-84/building 1, LUMC)

When What: Introduction to Molecular Epidemiology & R Who Where
09.00-09.45 Lecture: Introduction to FOS course Bas Heijmans J1-84
09.45-10.00 Break
10.00-10.45 Lecture: Introduction to Molecular Epidemiology: Large Scale Datasets Eline Slagboom J1-84
10.45-11.30 Lecture: Introduction to Large Scale Datasets: from SPSS to R Bas Heijmans J1-84
11.30-12.30 Lecture: Introduction to R Lucy Sinke J1-84
12.30-13.30 Lunch
13.30-15.00 Practical: Introduction to R: Basic Functionality (Answers) Lucy Sinke J1-84
15.00-15.15 Break
15.15-17.00 Practical: Introduction to R: Basic Functionality (Answers) Lucy Sinke J1-84

Tuesday October 22 (Location J1-84/building 1, LUMC)

When What: Further Introduction to R Who Where
09.00-10.00 Practical: Introduction to R: Visualizations & Statistics (Answers) Lucy Sinke J1-84
10.00-10.15 Break
10.15-12.30 Practical: Introduction to R: Visualizations & Statistics (Answers) Lucy Sinke J1-84
12.30-13.30 Lunch
13.30-15.00 Practical: Introduction to R: Bioconductor (Answers) Lucy Sinke J1-84
15.00-15.15 Break
15.15-17.00 Practical: Introduction to R: Bioconductor (Answers) Lucy Sinke J1-84

Wednesday October 23 (Location J1-84/building 1, LUMC)

When What: Genetics Who Where
09.00-10.00 Lecture: Introduction to Genome-wide Association Marian Beekman J1-84
10.00-10.15 Break
10.15-12.00 Practical: Genome-wide Association Marian Beekman J1-84
12.00-13.30 Lunch
13.30-14.00 Lecture: Interim Evaluation of Participation and Interaction Marian Beekman J1-84
14.00-15.00 Practical: Genome-wide Association Marian Beekman J1-84
15.00-15.15 Break
15.15-17.00 Practical: Genome-wide Association Marian Beekman J1-84

Thursday October 24 (Location J1-84/building 1, LUMC)

When What: Transcriptomics Who Where
09.00-10.00 Practical: Genome-wide Association Marian Beekman J1-84
10.00-10.15 Break
10.15-12.30 Practical: Genome-wide Association Marian Beekman J1-84
12.30-13.30 Lunch
13.30-14.00 Lecture: Introduction to Transcriptomics Rodrigo C de Almeida J1-84
14.00-15.00 Practical: Statistical Analysis of Expression Data Rodrigo C de Almeida J1-84
15.00-15.15 Break
15.15-17.00 Practical: Statistical Analysis of Expression Data Rodrigo C de Almeida J1-84

Friday October 25 (Location J1-84/building 1, LUMC)

When What: Transcriptomics Who Where
09.00-10.15 Practical: Statistical Analysis of Expression Data Rodrigo C de Almeida J1-84
10.15-10.30 Break
10.30-11.15 Lecture: Finding Functional Relevant Genes Yolande Ramos J1-84
11.15-12.30 Practical: Finding Genes in Practice Yolande Ramos J1-84
12.30-13.30 Lunch
13.30-15.00 Practical: Finding Genes in Practice Yolande Ramos J1-84
15.00-15.15 Break
15.15-17.00 Practical: Finding Genes in Practice Yolande Ramos J1-84

Week 2

Monday October 28 (Location J1-84/building 1, LUMC)

When What: Post-GWAS Functional Follow-up Who Where
09.00-10.15 Self-study: Freedman et al. (2011) Ingrid Meulenbelt J1-84
10.15-10.30 Break
10.30-11.30 Paper discussion: Freedman et al. (2011) Ingrid Meulenbelt J1-84
11.30-12.30 Lecture: Functional Genomics Ingrid Meulenbelt J1-84
12.30-13.30 Lunch
When What: DNA Methylomics Who Where
13.30-14.30 Lecture: Introduction to the Epigenome Roderick Slieker J1-84
14.30-15.00 Practical: Tissues & 450K Methylation Chip Data Roderick Slieker J1-84
15.00-15.15 Break
15.15-17.00 Practical: Tissues & 450K Methylation Chip Data Roderick Slieker J1-84

Tuesday October 29 (Location J1-84/building 1, LUMC)

When What: DNA Methylomics Who Where
09.00-10.00 Practical: Tissues & 450K Methylation Chip Data Roderick Slieker J1-84
10.00-10.15 Break
10.15-12.30 Practical: Tissues & 450K Methylation Chip Data Roderick Slieker J1-84
12.30-13.30 Lunch
13.30-14.30 Lecture: DNA Methylation Signatures of Prenatal Famine Exposure Bas Heijmans J1-84
14.30-15.00 Practical: Tissues & 450K Methylation Chip Data Roderick Slieker J1-84
15.00-15.15 Break
15.15-17.00 Practical: Tissues & 450K Methylation Chip Data Roderick Slieker J1-84

Wednesday October 30 (Location J1-84/building 1, LUMC)

When What: Ageing Biomarkers: Clocks of Chronological and Biological Age Who Where
09.00-10.00 Lecture: Metabolomics as Biomarkers Eline Slagboom J1-84
10.00-10.15 Break
10.15-12.30 Paper Discussion: Marioni et al. (2016) Eline Slagboom J1-84
12.30-13.30 Lunch
When What: Metabolomics Who Where
13.30-14.30 Lecture: Introduction to Metabolomics Marian Beekman J1-84
14.30-15.00 Practical: Metabolomics Data Analyses Erik van den Akker J1-84
15.00-15.15 Break
15.15-17.00 Practical: Metabolomics Data Analyses Erik van den Akker J1-84

Thursday October 31 (Location J1-84/building 1, LUMC)

When What: Next Generation Sequencing Who Where
09.00-10.00 Lecture: Next Generation Sequencing Technology Yavuz Ariyurek J1-84
10.00-10.15 Break
10.15-11.15 Lab tour: Next Generation Sequencing Technology Yavuz Ariyurek J1-84
11.15-12.00 Lecture: Medical Sequencing (Principles Exome and WGA Sequencing) Ingrid Meulenbelt J1-84
12.00-12.30 Practical: Exome Sequencing Early Onset OA Yolande Ramos J1-84
12.30-13.30 Lunch
13.30-15.00 Practical: Exome Sequencing Early Onset OA Ingrid Meulenbelt J1-84
15.00-15.15 Break
15.15-17.00 Practical: Exome Sequencing Early Onset OA Ingrid Meulenbelt J1-84

Friday November 1 (Location J1-84/building 1, LUMC)

When What: Clustering Analysis Who Where
09.00-10.00 Lecture: Clustering Analysis Transcriptomic Data Marcel Reinders J1-84
10.00-10.15 Break
10.15-11.00 Lecture: Clustering Analysis Transcriptomic Data Marcel Reinders J1-84
11.00-12.30 Practical: Clustering Analysis Transcriptomic Data Marcel Reinders J1-84
12.30-13.30 Lunch
When What: Integrative approaches Who Where
13.30-14.15 Lecture: Integrated Analysis of Multiple -omics Data and MR Bas Heijmans J1-84
14.15-15.00 Practical: Hands on Integration of -omics Datasets: eQTLs, mQTLs, and MR Bas Heijmans J1-84
15.00-15.15 Break
15.15-17.00 Practical: Hands on Integration of -omics Datasets: eQTLs, mQTLs, and MR Bas Heijmans J1-84

Week 3

Monday November 4 (Location J1-84/building 1, LUMC)

When What: Single Cell RNA-Sequencing Who Where
09.00-17.00 Lecture: Single cell RNA-sequencing Ahmed Mahfouz J1-84
09.00-10.00 Practical: Single cell RNA-sequencing Ahmed Mahfouz J1-84
10.00-10.15 Break
10.15-12.30 Practical: Single cell RNA-sequencing Ahmed Mahfouz J1-84
12.30-13.30 Lunch
13.30-15.00 Practical: Single cell RNA-sequencing Indu Khatri J1-84
15.00-15.15 Break
15.15-17.00 Practical: Single cell RNA-sequencing Indu Khatri J1-84

Tuesday November 5 (Location J1-84/building 1, LUMC)

When What: Databases and Reproducibility Who Where
09.00-10.00 Lecture: Databases Bas Heijmans J1-84
10.00-10.15 Break
10.15-12.30 Practical: Using Online Databases: Age and Methylation Bas Heijmans J1-84
12.30-13.30 Lunch
When What: Animal models on ageing Who Where
13.30-14.00 Lecture: Mouse model of Ageing Vered Raz J1-84
14.00-15.15 Self Study: Mouse model of Ageing Vered Raz J1-84
15.15-15.30 Break
15.30-17.00 Mouse model of Ageing: Presentation and Discussion Vered Raz J1-84

Wednesday November 6 (Location J1-84/building 1, LUMC)

When What: Research Findings Who Where
09.00-10.00 Free Self ###
10.00-10.15 Break
10.15-12.30 Free Self ###
12.30-13.30 Lunch
13.30-15.00 From Ideas to Study: Vandenbroucke and Pearce (2018) Suzanne Cannegieter V5-39
15.00-15.15 Break
15.15-17.00 From Ideas to Study: Vandenbroucke and Pearce (2018) Suzanne Cannegieter V5-39

Part 2: Applying Acquired Knowledge and Skills to Ageing.

Students will apply newly acquired skills to write a research proposal that follows a data science approach. This proporal will focus on ageing as a key example of a complex human trait. Students will work on developing a project proposal in pairs. Generating pilot data to support hypotheses by analyzing available real -omics data sets will be an integral part of the project proposal. During the week, there will be regular moments of interaction with the module coordinators and the opportunity to contact other tutors of the course.


Thursday November 7 (Location J1-84/building 1, LUMC)

When What: Introduction to Developing Project Proposal Who Where
09.00-10.00 Project Proposal: Where does Research Start. Part 1 Eline Slagboom J1-84
10.00-10.15 Break
10.15-11.00 Project Proposal: Where does Research Start. Part 2 Eline Slagboom J1-84
11.00-12.00 Work on the Project Proposal: Formulation of Hypothesis Self J1-84
12.00-13.00 Lunch
13.00-15.00 Work on the Project Proposal: Formulation of Objectives Self J1-84
15.00-15.15 Break
15.15-17.00 Work on the Project Proposal: Formulation of Objectives Self J1-84

Friday November 8 (Location J1-84/building 1, LUMC)

When What: Final assignment Who Where
09.00-17.00 Work on the Project Proposal Self J1-84

Monday November 11 (Location J1-84/building 1, LUMC)

When What: Final assignment Who Where
09.00-17.00 Work on the Project Proposal Self J1-84

Tuesday November 12 (Location J1-84/building 1, LUMC)

When What: Final assignment Who Where
09.00-17.00 Work on the Project Proposal Self J1-84

Wednesday November 13 (Location J1-84/building 1, LUMC)

When What: Final assignment Who Where
09.00-17.00 Work on the Project Proposal Self J1-84
17.00-23.59 Hand in Synopsis Project Proposal (Blackboard) Self J1-84

Thursday November 14 (Location J1-84/building 1, LUMC)

When What: Final assignment Who Where
09.00-12.30 Work on the Project Proposal Self J1-84
12.00-13.00 Lunch
13.00-17.00 Oral Presentation and Defense of Project Proposal All V3-18/22

Friday November 15 (Location J1-84/building 1, LUMC)

When What Final assignment Who Where
09.00-13.00 Self study Self J1-82
13.00-15.00 Reflective Assignment All J1-82
15:00 End of course