TRANSCRIPTOMICS 30 days · 6 modules · Online

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

Cluster cell types, discover novel subpopulations and trace developmental trajectories from single-cell transcriptomes.

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About this workshop

A tissue is a mixture of many cell types, and bulk sequencing averages them together. Single-cell RNA-Seq measures expression in each cell separately, so rare populations, cell states and developmental paths become visible. The data is large and noisy, which makes careful quality control and sensible choices at each step essential. This workshop walks through that process: filtering out poor-quality cells and doublets, normalising counts, reducing the data to its main patterns, grouping cells into clusters, finding the marker genes that define each group and labelling cell types. Later modules cover combining samples, comparing conditions within a cell type and ordering cells along a trajectory. By the end you will have an annotated map of the cells in a real dataset and the reasoning to defend it.

Tools and pipelines you will use

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

Cell Ranger ↗Seurat ↗Scanpy ↗DoubletFinder ↗Harmony ↗SingleR ↗Monocle 3 ↗

What you will learn

Module 1 Foundations
Week 1
Single-cell technologies How droplet and plate methods capture cells.
Data structure Cells, genes, barcodes and count matrices.
Setting up the environment Run R or Python tools for single-cell work.
Raw data processing Turn sequencing output into a cell-by-gene matrix.
Module 2 Quality control
Cell filtering Remove empty droplets, damaged cells and doublets.
Gene filtering Keep informative genes.
Ambient RNA and artefacts Recognise and reduce background signal.
QC reports Summarise quality per sample.
Module 3 Normalization and structure
Normalization Make cells comparable despite depth differences.
Variable genes Select genes that carry biological signal.
Dimensionality reduction PCA, UMAP and what they do and do not show.
Neighbour graphs Build the basis for clustering.
Module 4 Clusters and cell types
Clustering Group similar cells and choose a resolution.
Marker genes Find genes that define each cluster.
Cell-type annotation Label clusters using markers and references.
Cluster stability Check that groups are real, not artefacts.
Module 5 Comparisons and trajectories
Multi-sample integration Combine datasets and correct batch effects.
Differential expression between groups Compare conditions within cell types.
Trajectory analysis Order cells along development or response.
Cell communication basics Explore signalling between cell groups.
Module 6 Mini-project and report
Week 4
Project dataset Analyse a public single-cell dataset end to end.
Reproducible workflow Keep code, settings and versions together.
Figures and write-up Present clusters, markers and findings.
Review and next steps Discuss validation and 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 RNA-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 master cell filtering, doublet detection, normalization, PCA, UMAP embedding, Louvain/Leiden clustering, automated cell type annotation with SingleR, batch integration with Harmony, and pseudotime trajectory reconstruction with Monocle 3.

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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