About :
Master cutting-edge single-cell RNA-seq analysis with AI integration.
Aim :
This 3-day virtual workshop equips researchers with advanced skills in single-cell RNA-seq analysis (2024 standards), covering preprocessing, multi-omics integration, and spatial transcriptomics. Participants will leverage latest tools (Seurat 5.0, scVI, CellChat 2.0) to analyze real datasets, address batch effects, and predict cell trajectories. With hands-on sessions in R/Python, attendees will learn to integrate AI-driven methods (e.g., federated learning for collaborative atlases) while tackling ethical challenges like dataset bias. By blending theory with live demos (10x Visium HD, scATAC-seq), the workshop bridges wet-lab and computational genomics, empowering scientists to accelerate discoveries in immunology, cancer, and developmental biology.
Job Opportunity :
Single-Cell Bioinformatician – Core labs, biotech (10x Genomics, Parse Biosciences).Spatial Omics Specialist – Cancer centers, pharma (e.g., Genentech).Computational Biologist – Immunology/drug discovery (Allen Institute, Regeneron).AI-Genomics Scientist – Develop federated learning tools (Owkin, NVIDIA).Science Communicator – Translate scRNA-seq findings for CROs/journals.
Objective :
Process raw scRNA-seq data using Cell Ranger 7.0 and kb-python .
Perform AI-powered batch correction (scVI, Harmony) and clustering (Seurat 5.0).
Annotate cell types with automated tools (SingleR, Azimuth 2024 references).
Model cell trajectories using RNA velocity (scVelo, Dynamo).
Integrate multi-omics data (scRNA-seq + scATAC-seq) via WNN.
Analyze spatial transcriptomics (Visium HD) with Giotto/SpaceMarkers.
Detect dataset biases and apply FAIR data principles.
Your Mentor Details
Duration :
Start Date : 17/05/2025 -
End Date : 19/05/2025
Product Structure :
Day 1: Foundations & Latest Wet-Lab-to-Computational Pipelines
Pre-processing & QC
Latest tools: Cell Ranger 7.0 (10x Genomics) + kb-python for ultra-fast alignment
2024 focus: Handling multi-modal data (CITE-seq, ATAC-seq integration)Hands-on: QC metrics (mitochondrial reads, doublet detection) with SoupX & Scrublet
Normalization & Batch Correction
Emerging methods: GLM-based normalization (replacing log-Normalize)Hot topic: AI-driven batch correction (e.g., scVI vs Harmony)
Day 2: Advanced Clustering & Trajectory Analysis
Clustering & Annotation
Latest algorithms: Seurat 5.0’s graph-based clustering improvementsAuto-annotation tools: SingleR + Celldex (with 2024 reference datasets)Hands-on: Cluster PBMCs using Azimuth’s updated immune cell atlas
Trajectory & Dynamics
Trending: RNA velocity with scVelo + Dynamo for fate predictionBreakthrough: Time-resolved scRNA-seq (neural crest cell migration studies)
Day 3: Multi-Omics Integration & Spatial Transcriptomics
Multi-Omics
Cutting-edge: Weighted Nearest Neighbor (WNN) in Seurat v52024 focus: Paired scRNA-seq + scATAC-seq analysis
Spatial Transcriptomics
Latest platforms: 10x Visium HD (2μm resolution)Tools: Giotto + SpaceMarkers for niche detectionHot research: Cell-cell interaction prediction with CellChat 2.0
Ethics & Reproducibility
FAIR data: Using Dragonn for automated metadata taggingAI bias: Addressing dataset imbalances in cell atlases
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Benefits to the participants :
Unlock 2024’s most in-demand scRNA-seq skills for academia/industry.Analyze data 10x faster with optimized pipelines (Seurat 5.0, Scanpy).Decode complex biology through multi-omics and spatial tools.Navigate AI ethics in single-cell research (bias, reproducibility).Access pre-configured notebooks and curated reference datasets.
Outcomes :
Process and visualize 10x Genomics/Visium HD datasets independently.
Generate publication-ready figures (UMAPs, trajectory plots, spatial maps).
Build a reproducible scRNA-seq workflow with version control (Git).
Propose a mini research project using workshop tools.
Join a global community of single-cell researchers.
