Data Analysis in Infectious Disease Genomics
( 30 Modules )

Module #1
Introduction to Infectious Disease Genomics
Overview of infectious diseases, genomics, and the importance of data analysis in understanding disease transmission and prevention

Module #2
Genomic Data Types and Sources
Introduction to different types of genomic data (e.g. WGS, WES, RNA-seq) and sources (e.g. NCBI, ENA, GenBank)

Module #3
Bioinformatics Tools for Genomic Data Analysis
Overview of command-line tools and web-based platforms for genomic data analysis (e.g. BLAST, FASTQ, Trimmomatic)

Module #4
Quality Control and Preprocessing of Genomic Data
Assessing data quality, trimming, filtering, and preprocessing genomic data for analysis

Module #5
Genome Assembly and Annotation
Introduction to genome assembly and annotation, including tools and workflows (e.g. SPAdes, Prokka)

Module #6
Phylogenetic Analysis of Genomic Data
Introduction to phylogenetic analysis, including tree building and interpretation (e.g. RAxML, FigTree)

Module #7
Inferring Transmission Dynamics from Genomic Data
Using genomic data to infer transmission dynamics, including cluster analysis and molecular clock methods

Module #8
Genomic Epidemiology of Bacterial Infectious Diseases
Case studies of genomic epidemiology in bacterial infectious diseases (e.g. tuberculosis, MRSA)

Module #9
Genomic Epidemiology of Viral Infectious Diseases
Case studies of genomic epidemiology in viral infectious diseases (e.g. influenza, HIV)

Module #10
Genomic Epidemiology of Parasitic Infectious Diseases
Case studies of genomic epidemiology in parasitic infectious diseases (e.g. malaria, leishmaniasis)

Module #11
Variant Calling and Functional Annotation
Introduction to variant calling and functional annotation, including tools and workflows (e.g. GATK, SnpEff)

Module #12
Association Analysis of Genomic Data with Phenotypic Traits
Introduction to association analysis, including genome-wide association studies (GWAS) and Mendelian randomization

Module #13
Machine Learning in Infectious Disease Genomics
Introduction to machine learning methods for classification, clustering, and regression in infectious disease genomics

Module #14
Visualization and Communication of Genomic Data
Effective visualization and communication of genomic data results, including dashboards and reports

Module #15
Data Management and Integration in Infectious Disease Genomics
Best practices for data management, integration, and sharing in infectious disease genomics

Module #16
Ethical and Regulatory Considerations in Infectious Disease Genomics
Ethical and regulatory considerations in infectious disease genomics, including data privacy and sharing

Module #17
Computational Resource Management for Genomic Data Analysis
Managing computational resources for large-scale genomic data analysis, including HPC and cloud computing

Module #18
Case Studies in Infectious Disease Genomics
In-depth case studies of infectious disease genomics projects, including data analysis and interpretation

Module #19
Collaborative Workflows in Infectious Disease Genomics
Collaborative workflows and team science in infectious disease genomics, including version control and issue tracking

Module #20
Advanced Topics in Infectious Disease Genomics
Advanced topics in infectious disease genomics, including pangenomics, transcriptomics, and proteomics

Module #21
Current Challenges and Future Directions in Infectious Disease Genomics
Current challenges and future directions in infectious disease genomics, including emerging technologies and applications

Module #22
Grant Writing and Funding Opportunities in Infectious Disease Genomics
Grant writing and funding opportunities in infectious disease genomics, including NIH and international funding agencies

Module #23
Science Communication and Policy in Infectious Disease Genomics
Science communication and policy in infectious disease genomics, including science writing and policy briefs

Module #24
Capstone Project:Genomic Analysis of an Infectious Disease Outbreak
Apply course concepts to a real-world infectious disease outbreak, including data analysis, interpretation, and presentation

Module #25
Peer Review and Feedback in Infectious Disease Genomics
Peer review and feedback in infectious disease genomics, including critical evaluation of scientific manuscripts and presentations

Module #26
Career Development and Professional Networking in Infectious Disease Genomics
Career development and professional networking in infectious disease genomics, including job market trends and opportunities

Module #27
Interdisciplinary Collaboration in Infectious Disease Genomics
Interdisciplinary collaboration in infectious disease genomics, including epidemiology, clinical medicine, and public health

Module #28
Global Health and Infectious Disease Genomics
Global health perspectives on infectious disease genomics, including international collaborations and resource sharing

Module #29
Infectious Disease Genomics in Low-Resource Settings
Challenges and opportunities in applying infectious disease genomics in low-resource settings

Module #30
Course Wrap-Up & Conclusion
Planning next steps in Data Analysis in Infectious Disease Genomics career

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Data Analysis in Infectious Disease Genomics ( 30 Modules )

Data Analysis in Infectious Disease Genomics
( 30 Modules )