Nanopore DNA Sequencing with AI Tools: From Raw Signals to Genomic Insights

To equip participants with practical knowledge of Nanopore DNA sequencing and AI-assisted genomic analysis workflows for real-time sequencing, genome correction, metagenomic classification, variant discovery, and epigenetic interpretation.

• To introduce the fundamentals of Nanopore DNA sequencing and long-read sequencing technologies.
• To explain how raw Nanopore signals are converted into genomic information using AI-based basecalling.
• To familiarize participants with key tools used in Nanopore read processing, alignment, and assembly.
• To demonstrate AI-assisted consensus polishing using Medaka.
• To introduce metagenomic species classification using Kraken2, Bracken, and Krona.
• To explain deep learning-based variant calling using Clair3.
• To demonstrate direct DNA methylation analysis using Dorado methylation models and Modkit.
• To help participants interpret sequencing results for biological, clinical, and environmental applications.

📅 Day 1: Nanopore Sequencing Fundamentals, Basecalling & Genome Assembly

• Introduction to Long-Read Sequencing Technologies and Nanopore DNA Sequencing
• Principles of Nanopore Sequencing and Real-Time Portable Genomics
• Comparison of Nanopore Sequencing with Short-Read Sequencing Platforms
• Raw Signal Generation and FAST5/POD5 Data Formats
• AI-Based Basecalling and Signal Interpretation Using Dorado
• FASTQ Files, Read Quality Assessment, and Read Filtering
• Read Alignment Using Reference Genomes with Minimap2
• Genome Assembly from Long-Read Nanopore Sequencing Data Using Flye
• Applications in Microbial Genomics, Clinical Genomics, Agriculture, and Environmental Monitoring

🧰 AI Tools Covered:

• Dorado: AI-based Nanopore basecalling tool
• Minimap2: Long-read alignment tool
• Flye: Long-read genome assembly tool
• NanoPlot / NanoFilt: Read quality analysis and filtering tools

🛠️ Hands-on:

• Hands-on 1: Participants will assess Nanopore sequencing read quality, read length distribution, and sequencing output using quality control tools.
• Hands-on 2: Participants will understand how long reads are assembled into draft genomes using Nanopore sequencing datasets.

✅ Expected Outcome:

• By the end of Day 1, participants will understand the basic Nanopore sequencing workflow, AI-based basecalling, read quality assessment, alignment, and genome assembly.

📅 Day 2: AI-Assisted Genome Polishing & Metagenomic Classification

• Introduction to Genome Polishing in Long-Read Sequencing
• Sources of Errors in Nanopore Sequencing Reads
• Role of Neural Networks in Consensus Correction
• AI-Assisted Genome Polishing Using Medaka
• Importance of Polished Assemblies in Microbial Genomics
• Introduction to Metagenomics Using Nanopore Sequencing
• Real-Time Pathogen Detection and Environmental Surveillance
• AI-Supported Adaptive Sampling and Read Classification Concepts
• Taxonomic Classification of Microbial Reads
• Abundance Estimation and Microbial Community Interpretation
• Visualization of Taxonomic Classification Results

🧰 AI Tools Covered:

• Medaka: Neural network-based consensus polishing tool
• Kraken2: Metagenomic read classification tool
• Bracken: Species abundance estimation tool
• Krona: Interactive visualization of taxonomic results

🛠️ Hands-on:

• Hands-on 3: Participants will learn how AI-assisted polishing improves genome assembly accuracy from Nanopore reads using Medaka.
• Hands-on 4: Participants will classify microbial sequencing data and visualize microbial composition using taxonomic charts.

✅ Expected Outcome:

• By the end of Day 2, participants will understand how AI-assisted tools support genome correction, microbial classification, pathogen identification, and environmental surveillance.

📅 Day 3: AI-Based Variant Calling and Epigenetic Analysis

• Introduction to Genomic Variants: SNVs, Insertions, and Deletions
• Challenges of Variant Calling in Long-Read Sequencing
• Role of Deep Learning in Variant Detection
• Clair3 Architecture: Pileup and Full-Alignment Models
• Applications in Rare Disease Research, Microbial Genomics, and Clinical Genomics
• Introduction to Epigenetics and DNA Methylation
• Direct Detection of Methylation Using Nanopore Signal Data
• AI-Based Identification of 5mC, 5hmC, and 6mA Modifications
• Applications in Diagnostics, Cancer Biology, and Biopharma Research
• Visualization and Interpretation of Variant and Methylation Results

🧰 AI Tools Covered:

• Clair3: Deep learning-based variant calling tool
• Dorado Methylation Models: AI-based methylation detection
• Modkit: Methylation frequency extraction and analysis
• IGV: Genome visualization tool

🛠️ Hands-on:

• Hands-on 5: Participants will learn how AI-based variant calling generates VCF files from Nanopore sequencing data using Clair3.
• Hands-on 6: Participants will understand how methylation signals can be detected directly from Nanopore data using Dorado/Modkit and interpreted for biological insights.

✅ Expected Outcome:

• By the end of Day 3, participants will understand how deep learning tools are used for variant calling, epigenetic analysis, and biological interpretation in Nanopore sequencing workflows.

• Students from biotechnology, bioinformatics, life sciences, microbiology, genomics, and related fields
• Ph.D. scholars and researchers working in genomics, sequencing, microbiology, or computational biology
• Faculty members and academicians interested in AI-assisted genomic workflows
• Clinical genomics and molecular diagnostics professionals
• Researchers working in infectious disease surveillance, environmental genomics, and microbial genomics
• Industry professionals from biotech, pharma, diagnostics, and sequencing-based research domains

By the end of this workshop, participants will be able to:

• Understand the complete Nanopore DNA sequencing workflow.
• Explain how AI supports basecalling, read correction, classification, variant calling, and methylation detection.
• Perform basic Nanopore read quality assessment.
• Understand genome assembly and AI-assisted polishing workflows.
• Classify microbial communities using Nanopore metagenomic data.
• Interpret species abundance and taxonomic visualization outputs.
• Understand deep learning-based variant calling using Clair3.
• Explore direct methylation detection using Nanopore signal data.
• Apply Nanopore AI workflows in genomics, diagnostics, pathogen detection, and environmental surveillance.