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Course 5: Causal Inference in Genomics: A Deep Dive into GWAS and Mendelian Randomisation
Course 5: Causal Inference in Genomics: A Deep Dive into GWAS and Mendelian Randomisation
Overview
Overview
Mode of Communication: Bangla
Duration: 12 Weeks (3 months) and project
Frequency: Once a week (Saturday)
Live Session Time:
Lecture (2 hours):
Bangladesh Time: 8:00 PM ~ 10:00 PM
USA Pacific Time (CA/OR/WA): 8:00 AM ~ 10:00 AM
UK Time: 3:00 PM ~ 5:00 PM
Total Classes: ~ 30 hours of live lectures and support
Assignments: Weekly Problem Solving exercise
Coding Support: Engagement Through Google Classroom
Projects: Hands-on, comprehensive projects
Contact: oxfordbiodiscoveryventures@gmail.com
Prerequisites: Prior experience with GWAS or Mendelian randomisation is not required. However, participants should have an understanding of fundamental concepts in epidemiology, biostatistics, genetics, and basic data analysis.
Certificates will be provided after successful completion of the course
Certificates will be provided after successful completion of the course
Module 1
Module 1
Introduction to Genetic Epidemiology
Introduction to Genetic Epidemiology
Week 1: Fundamentals of epidemiology, biostatistics, Introduction to R and data
analysis with R
Week 2: Basic genetic epidemiology (molecular genetics, alleles, genotype,
phenotype, familial risk, heritability, study designs, rare vs. common diseases)
Module 2
Module 2
Genome-Wide Association Studies (GWAS)
Genome-Wide Association Studies (GWAS)
Week 3: Fundamentals of GWAS; introduction to PLINK (download, installation,
setup)
Week 4: GWAS Practical, Part 1 – Pre-GWAS quality control and running GWAS
Week 5: GWAS Practical, Part 2 – Multiple testing, visualising and checking GWAS
results, confounding & population stratification, covariate adjustment
Week 6: GWAS Practical, Part 3 – Post-GWAS analysis for biological insights
(linkage disequilibrium, phenome-wide association studies, colocalisation, fine-
mapping, functional genomics)
Module 3
Module 3
Mendelian Randomisation (MR)
Mendelian Randomisation (MR)
Week 7: Core concepts of Mendelian randomisation
o Practical: MR using individual-level data in R
Week 8: Summary data and two-sample MR; key assumptions; statistical
considerations
o Practical: Comparing individual-level vs. summary data in R
Week 9: Robust methods with summary data (Inverse Variance Weighted method,
MR-Egger regression, median-based estimation, mode-based estimation, and recent
methods); choosing instruments for MR
o Practical: Paper discussion
Week 10: Multivariable MR; interpretation of causal effects; using genetic data to
predict drug effects
o Practical: MR using specialised software
Week 11: Project/assignment involving statistical and bioinformatics analysis, and
interpretation of results
Week 12: Final project presentations and discussions; project idea development;
careers in genomics; additional tools (Python, Linux); and pathways for future
learning
Instructor
Instructor
Nazmul Sarwar
MPhil in Population Health Sciences,
University of Cambridge
PhD Student in Medical Sciences,
University of Cambridge
Follow Us
Follow Us
Address
Address
Oxford, Oxfordshire,
United Kingdom
Email
Email
oxfordbiodiscoveryventures@gmail.com
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