Bioinformatics Training Workshop for AMR Surveillance

 
About the Training
KIRCT, in partnership with the GHRU, is hosting a comprehensive Bioinformatics Training Workshop to strengthen capacity for genomic surveillance of AMR. The training will run from 6th to 25th October 2025 and will feature a combination of lectures, demonstrations, and hands-on analysis sessions led by experienced bioinformaticians and microbiologists.
 
Description of the Training
This intensive workshop is designed to equip participants with the essential knowledge and practical skills to analyze microbial genomic data for AMR surveillance. The training will cover key aspects including data quality control, genome assembly, phylogenetic analysis, AMR gene detection, plasmid analysis, and data visualization. Participants will also learn how to use GitHub for collaborative genomic analysis and how to integrate genomic findings with phenotypic AMR data.
Topics include:
  • Introduction to Bioinformatics, Databases, and Microreact Visualization
  • Tool Installation & Environment Setup
  • Quality Control, Trimming, MultiQC
  • Genome Assembly (SPAdes, ConFinder, BactInspector) and Phylogenetics (Snippy)
  • AMR Gene Detection (AMRFinderPlus, PlasmidFinder) and Interpretation
  • GitHub Basics, MLST, and SNP Phylogeny Batch Runs
Target Audience
The training is intended for:
  • Microbiologists and molecular biologists at KIRCT
  • Genomics and bioinformatics personnel
  • Clinicians and laboratory scientists involved in AMR surveillance
  • Interns and postgraduate students interested in microbial genomics and public health research
Learning Objectives
By the end of the training, participants will be able to:
  • Understand the principles and applications of bioinformatics in microbial genomic surveillance
  • Perform quality control, genome assembly, and phylogenetic analyses of bacterial sequence data
  • Detect and interpret antimicrobial resistance genes and plasmids using standard bioinformatics tools
  • Use data visualization platforms to explore and communicate genomic data
  • Apply GitHub for collaborative workflows and reproducible genomic analysis
  • Integrate genomic data with phenotypic resistance profiles to support AMR surveillance and research