Single-Cell Omics Analysis & Integration — Hands-on

Gain expertise in single-cell omics analysis and integration: scRNA-seq and scATAC-seq QC, clustering, annotation, cross-modal integration, trajectories, and velocity.

Single-Cell Omics Analysis & Integration

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Session Index

Session 1 — scRNA-seq QC & Preprocessing Session 2 — Clustering, Annotation & DE Session 3 — Multi-omics, Trajectories & Velocity Session 4 — Mini Capstone: scOmics Pipeline

Session 1

Fee: Rs 6300

scRNA-seq QC & Preprocessing

Read processing, mapping and quantification choices

Cell Ranger STARsolo Alevin-fry

QC metrics, filtering and ambient RNA removal

genes/cell UMIs/cell MT% SoupX

Doublet detection and normalization strategies

Scrublet DoubletFinder SCTransform log-normalize

Session 2

Fee: Rs 8400

Clustering, Annotation & DE

Dimensionality reduction and community detection

PCA UMAP/t-SNE Leiden/Louvain Scanpy/Seurat

Automated cell-type annotation and marker discovery

SingleR Azimuth CellTypist FindMarkers

Differential expression and enrichment overlays

rank_genes_groups GSEA/ORA KEGG/Reactome

Session 3

Fee: Rs 11200

Multi-omics, Trajectories & Velocity

scATAC-seq QC, peaks and gene activity matrices

FRiP/TSS enrichment MACS2 Signac/ArchR

Cross-modal integration and joint embeddings

Seurat WNN Harmony LIGER

Trajectory inference and RNA velocity views

Monocle 3 Slingshot PAGA scVelo

Session 4

Fee: Rs 14000

Mini Capstone: scOmics Pipeline

Design a reproducible scRNA-seq/scATAC-seq workflow with provenance

Theory

Automate ingest→QC→cluster→annotate→integrate→trajectory with reports

Snakemake Conda/Mamba Quarto/JupyterLab

Deliver annotated objects, dashboards and submission-ready metadata

Seurat/Scanpy pandas plotly

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Single-Cell Omics Analysis & Integration Training | Seurat/Scanpy, scRNA-seq & scATAC-seq

Single-Cell Omics Analysis & Integration — Hands-on