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Learning Objectives

After completing this workshop, participants will be able to:

Core Competencies

1. Pathogen Genomics Principles

  • Understand the principles of pathogen genomics and its role in infectious disease surveillance and control
  • Explain how genomic data complements traditional epidemiological approaches
  • Describe the impact of genomic surveillance on public health decision-making

2. Data Generation Workflow (Days 1-2)

  • Describe the complete workflow of genomic data generation, from sample collection to sequence analysis
  • Evaluate different sequencing technologies and their applications (Day 1)
  • Design appropriate sampling strategies for genomic surveillance
  • Navigate high-performance computing systems (Day 2)

3. Bioinformatics Analysis (Days 2-3)

  • Apply basic bioinformatics tools to analyze pathogen genomic data
  • Perform quality control, assembly, and annotation of microbial genomes (Days 2-3)
  • Execute MLST typing and serotyping for strain characterization (Day 3)
  • Implement reproducible analysis workflows using command-line tools

4. Epidemiological Applications (Day 4)

  • Interpret genomic data for epidemiological insights, including outbreak detection and tracking
  • Construct and interpret phylogenetic trees for transmission analysis (Day 4)
  • Perform pangenome analysis and comparative genomics (Day 4)
  • Integrate genomic and epidemiological data for outbreak investigation

5. Antimicrobial Resistance (Day 3)

  • Understand the role of genomics in identifying antimicrobial resistance mechanisms
  • Detect AMR genes and mutations in genomic data (Day 3)
  • Analyze mobile genetic elements and resistance spread (Day 3)
  • Predict resistance phenotypes from genomic data

6. Metagenomics (Days 5-6)

  • Apply metagenomic approaches to study microbial communities (Day 5)
  • Analyze microbiome composition and diversity metrics (Day 5)
  • Identify pathogens in complex microbial communities (Day 6)
  • Detect co-infections and community shifts (Day 6)

7. Advanced Analysis (Days 6-8)

  • Perform variant calling and mutation analysis (Day 6)
  • Establish genotype-phenotype correlations (Day 6)
  • Develop reproducible Nextflow pipelines (Days 7-8)
  • Optimize workflow performance and testing (Day 8)

8. Data Management and Reproducibility (Days 7-8)

  • Implement version control for research projects
  • Create reproducible analysis pipelines using workflow managers (Days 7-8)
  • Apply best practices for data management and sharing

9. Critical Analysis and Communication (Days 9-10)

  • Apply learned skills to real research data (Day 9)
  • Troubleshoot analysis challenges independently (Day 9)
  • Evaluate the quality and reliability of genomic analyses
  • Communicate genomic findings to diverse audiences
  • Present research findings effectively (Day 10)

Practical Skills

Participants will gain hands-on experience with:

  • Unix/Linux command-line interface
  • Git version control
  • Docker containerization
  • Nextflow workflow management
  • Popular bioinformatics tools and databases
  • Data visualization and interpretation
  • Scientific presentation and communication

Assessment Criteria

Progress will be evaluated through:

  • Completion of hands-on exercises
  • Quality of individual analysis projects
  • Participation in group discussions
  • Final project presentation
  • Understanding demonstrated in Q&A sessions