This five‑day virtual course offers a focused introduction to analysing single‑cell RNA sequencing (scRNA‑seq) data using Python and command‑line tools. It is designed for you if you are a researcher in biology, computational science, and data analysis who wants to understand and apply core scRNA‑seq workflows. You should have basic familiarity with the Unix command line and a foundational understanding of Python.

Throughout the course, we will guide you through the main steps of droplet‑based scRNA‑seq analysis, from raw sequencing reads to clustering and biological interpretation. You will learn about experimental design, data processing, quality control, normalisation, feature selection, dimensionality reduction, batch correction, clustering, marker gene identification, and differential expression. Additional sessions introduce spatial transcriptomics, trajectory analysis, multi‑omics integration, and the Single Cell Expression Atlas.

Training combines lectures, live discussions, and hands‑on exercises using EMBL‑EBI’s virtual infrastructure, allowing you to practise workflows without installing specialised software.

Virtual course

You will learn via a mix of pre-recorded lectures, live presentations, and trainer Q&A sessions. Practical experience will be developed through group activities and trainer-led computational exercises. Live sessions will be delivered using Zoom with additional support and asynchronous communication via Slack.

'Single-cell RNA-seq analysis with Python 2027' is currently in development. Sign up for alerts to hear as this course develops.