EPIGENOMICS 30 days · 6 modules · Online

Single-Cell ATAC-Seq Data Analysis Workshop (30-Day, Online)

Analyse open chromatin in single cells: QC, clustering, motif activity and multi-omic integration.

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About this workshop

Single-cell ATAC-Seq measures chromatin accessibility in individual cells, which lets you see which regulatory regions distinguish one cell type from another. The data is extremely sparse, because each cell contributes only a few thousand fragments, so it needs methods designed for that. This workshop introduces the data structure and the quality metrics used to filter cells, then shows how to reduce dimensions, correct batch effects, cluster cells and score gene activity from nearby accessible regions. You use these scores and known markers to name cell types, find regions specific to each group, and infer which transcription factors may drive them. A final module covers combining accessibility with single-cell RNA data and ordering cells along a trajectory.

Tools and pipelines you will use

This workshop emphasizes standard, open-source bioinformatics tools widely used in peer-reviewed genomics literature:

Cell Ranger ATAC ↗Signac ↗ArchR ↗Seurat ↗MACS3 ↗chromVAR ↗cisTopic ↗

What you will learn

Module 1 Foundations
Week 1
Single-cell chromatin concepts How accessibility is measured in single cells.
Data structure Cells, peaks, fragments and matrices.
Environment setup Run R or Python single-cell tools.
Fragment files Understand the main raw output.
Module 2 Quality control
Cell-level metrics Fragment count, enrichment and fragment size.
Filtering cells Remove low-quality cells and doublets.
Peak set definition Build a common set of regions.
QC summary Report quality per sample.
Module 3 Dimensionality reduction
Normalization for sparse data Handle very sparse counts.
Latent semantic indexing Reduce dimensions for chromatin data.
Embeddings Visualize cells with UMAP.
Batch effects Detect and reduce technical differences.
Module 4 Clusters and annotation
Clustering cells Group cells by accessibility.
Gene activity scores Estimate gene activity from nearby peaks.
Annotating clusters Name cell types using known markers.
Cluster-specific peaks Find regions that define each group.
Module 5 Regulators and integration
Motif activity Infer which factors drive each cluster.
Integrating with single-cell RNA-Seq Match chromatin to expression.
Linking peaks to genes Predict regulatory connections.
Trajectories Order cells by changing accessibility.
Module 6 Mini-project and report
Week 4
Project dataset Analyse a public single-cell ATAC dataset.
Reproducible workflow Record code, settings and versions.
Figures and write-up Present clusters and regulators.
Review and next steps Discuss follow-up experiments.

What you receive & prerequisites

What you receive

  • 30 days of structured online self-paced access & mentor guidance
  • Curated real-world NGS benchmark datasets
  • Reusable pipeline scripts and command-line code templates
  • Independent capstone mini-project evaluation
  • Certificate of Completion issued by Xenoi Biotech Pvt. Ltd.

Prerequisites & setup

  • Basic life science background (B.Sc., M.Sc., B.Tech, or research scholar)
  • No prior programming or Linux experience required (covered in Module 1)
  • Laptop or PC with 8 GB RAM and internet access
  • Remote compute setup instructions provided during onboarding

Course curriculum designed by Anjali Chaudhary, Bioinformatics Scientist at Xenoi Biotech.

Last updated: October 2026

Related workshops & services

Broaden your computational biology expertise with complementary workshops:

Need this analysis done for your laboratory data? Explore our Genomics Services or consult on Custom Bioinformatics Pipelines.

Frequently asked questions

Is this Single-cell ATAC-Seq workshop delivered online?

Yes. All Xenoi Biotech workshops are delivered 100% online, allowing researchers and students across India and internationally to participate with remote compute support.

How long is the workshop and what is the workload?

The workshop runs for 30 days across 6 structured modules. Learners typically dedicate 1 to 2 flexible hours per day to work through pipeline commands, code exercises, and the mini-project.

Who is this workshop designed for?

It is built for B.Sc., M.Sc., and Ph.D. students, postdoctoral researchers, faculty members, and industry professionals in biotechnology, biochemistry, microbiology, and medicine who need to analyze NGS datasets independently.

What will I learn in this workshop?

You will learn single-cell chromatin preprocessing with Cell Ranger ATAC and Signac, cell filtering by TSS enrichment and nucleosome banding, iterative LSI dimensionality reduction, cluster annotation via gene activity scores, chromVAR motif enrichment, and trajectory inference.

What are the fees, dates, and enrollment details?

The workshop fee is MRP ₹5,000, inclusive of GST. Batch dates are shared on enquiry. Use the Enrol now button to reserve your place or receive the upcoming schedule.

Fees, dates and batches

The workshop fee is MRP ₹5,000 (incl. GST). Batch dates and onboarding materials are shared upon enquiry.

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