Workshop: Single Cell Data Analysis With Python

Wednesday 28 January | 16:10 - 17:40 | Workshop Room S15

Want to learn how to analyse single-cell data? Good at Python? Listen up!  

If you’re a Python coder and completely new to single-cell analysis, then this is for you! Whether you have a single-cell project on the horizon or simply want to expand your bioinformatics toolkit, this workshop will give you a solid foundation.  

In this hands-on workshop, we will introduce you to the Python ecosystem for single-cell, explain the analytical considerations for single-cell analysis, and showcase an end-to-end suggested processing workflow. We will explain how and why each step is done so that you leave with a conceptual understanding.

Daniel Snell, Hubert Slawinski from the Crick Genomics Platform will be around too for single cell chats about bench data generation and analysis.  

Image of dna and a scientist

Why Attend

Learning objectives

  • Explore and manipulate single-cell data using Scanpy and  Anndata.  

  • Perform QC, data viz and exploratory analysis of single-cell data in Python. 

  • Annotate cell-types via atlas-based label transfer using Celltypist. 

  • Understand scvi-tools ecosystem. 

  • Identify and evaluate key decision points and considerations (eg, cell cycle regression, doublet detection, sample integration). 

Who should attend

  • You should have 3+ years of Python experience (comfortable with Python (functions, pandas/numpy, debugging independently). 

  • Prior sc-RNAseq experience NOT required.   

  • Working Laptop with Python installed. 

  • A virtual env set up (uv, conda) and ready, if you would like to code along. 

What to expect

  • Warning: Due to the time limit on this workshop, if you attend without being proficient in Python, you will struggle to keep up.

  • There will not be time for debugging basic Python syntax during the workshop.

  • The main focus is on demystifying a single-cell analysis workflow using Python as the chosen language.