Introduction

Genetic Epidemiology is an advanced and rapidly evolving field that integrates genetics, biostatistics, bioinformatics, and population health sciences to understand the role of genetic factors in disease distribution and determinants in populations. Genetic Epidemiology Training Course is designed to equip learners with cutting-edge competencies in genome-wide association studies (GWAS), polygenic risk scoring, precision medicine, molecular epidemiology, and computational genomics. With the rise of big data in healthcare, AI-driven genomics, and personalized medicine, genetic epidemiology has become a cornerstone in modern biomedical research and public health decision-making.

This course provides a structured pathway for mastering both theoretical foundations and practical applications of genetic data analysis, disease mapping, heritability estimation, and causal inference in complex traits. Participants will engage with real-world datasets and advanced analytical tools used in global research institutions. The program emphasizes data-driven health innovation, translational genomics, and population-based genetic research, enabling learners to contribute to breakthroughs in disease prevention, drug discovery, and global health surveillance systems.

Programme Curriculum

Genetic Epidemiology Training Course

Introduction

Course Duration

5 days

Course Objectives

Understand fundamentals of genetic epidemiology and molecular genetics in population health
Apply Genome-Wide Association Studies (GWAS) methodologies in research
Analyze polygenic risk scores (PRS) for complex diseases
Develop skills in bioinformatics pipelines and genomic data processing
Interpret heritability and gene-environment interactions
Use R, Python, and Bioconductor for genetic data analysis
Conduct causal inference using Mendelian Randomization
Evaluate precision medicine and personalized healthcare models
Understand epigenetics and gene regulation mechanisms
Apply statistical genetics and multivariate analysis techniques
Integrate omics data (genomics, transcriptomics, proteomics)
Design and interpret population-based genetic studies
Translate research findings into public health genomics interventions

Target Audience

Public health professionals
Medical doctors and clinical researchers
Epidemiologists and biostatisticians
Geneticists and molecular biologists
Bioinformatics analysts and data scientists
Pharmaceutical and biotech researchers
Graduate students in biomedical sciences
Health policy makers and global health practitioners

Course Modules

Module 1: Foundations of Genetic Epidemiology

Basics of human genetics and inheritance patterns
Introduction to population genetics and allele frequency
Study designs in genetic epidemiology
Hardy-Weinberg equilibrium applications
Data sources in genomic research
Case Study: Mapping genetic susceptibility of sickle cell disease in African populations

Module 2: Genome-Wide Association Studies (GWAS)

GWAS principles and workflows
SNP identification and genotyping techniques
Quality control in genomic datasets
Statistical significance and multiple testing correction
Visualization of GWAS results (Manhattan plots)
Case Study: GWAS analysis of Type 2 Diabetes risk variants

Module 3: Bioinformatics & Genomic Data Analysis

Introduction to bioinformatics tools and databases
Sequence alignment and annotation techniques
Variant calling and filtering pipelines
Use of R/Python in genomic analysis
Data storage and cloud genomics
Case Study: Cancer mutation profiling using TCGA datasets

Module 4: Statistical Genetics & Causal Inference

Regression models in genetic studies
Heritability estimation methods
Mendelian Randomization techniques
Confounding and bias control
Bayesian approaches in genetics
Case Study: Causal role of BMI genes in cardiovascular disease

Module 5: Polygenic Risk Scores & Predictive Genetics

Construction of polygenic risk scores
Risk prediction models
Clinical applications of PRS
Validation of predictive models
Integration into healthcare systems
Case Study: Predicting Alzheimer’s disease risk using PRS

Module 6: Epigenetics & Gene Regulation

DNA methylation and histone modification
Environmental influence on gene expression
Epigenome-wide association studies (EWAS)
Developmental epigenetics
Epigenetic biomarkers in disease
Case Study: Impact of smoking on epigenetic changes in lung cancer

Module 7: Precision Medicine & Translational Genomics

Principles of precision medicine
Pharmacogenomics applications
Drug-gene interaction mapping
Clinical decision support systems
Personalized treatment strategies
Case Study: Targeted cancer therapy using genomic profiling

Module 8: Public Health Genomics & Big Data Integration

Genomic surveillance systems
Integration of multi-omics data
AI and machine learning in genomics
Ethical, legal, and social implications (ELSI)
Global health genomics strategies
Case Study: COVID-19 variant tracking using genomic surveillance

Training Methodology

This course employs a participatory and hands-on approach to ensure practical learning, including:

Interactive lectures and presentations.
Group discussions and brainstorming sessions.
Hands-on exercises using real-world datasets.
Role-playing and scenario-based simulations.
Analysis of case studies to bridge theory and practice.
Peer-to-peer learning and networking.
Expert-led Q&A sessions.
Continuous feedback and personalized guidance.

Register as a group from 3 participants for a Discount

Send us an email: info@fineskilltrainingcenter.org or call +254769199797

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to Fineskill Training Center account, as indicated in the invoice so as to enable us prepare better for you.

Skills & Software Covered

Genetic risk analysis Heritability studies Molecular epidemiology Statistical genetics

Programme Fee

Duration: 5 Days

Method: Online or Physical

Online Price: $1,000

Physical Price: $1,500

Certification: Accredited Certificate

View Available Dates 📄 Download Course Outline (PDF)

Available Sessions

Location

Month

Year

Oct 19 2026

19 Oct — 23 Oct 2026

💻 Online / Virtual session

Online $1,000