Course Content

These materials were part of the live ‘Single-Cell RNA-seq Analysis using Python’ course which took place in February 2025. Please refer to the course page and programme to check details about this live event and the original programme.

The content table below outlines the different sessions that were included in the course, as well as the format of the materials (slides/videos/practicals) and each session’s trainer. Either proceed through the materials using the arrows at the end of each page or pick your topic of interest from the table below to skip straight to it.

All the data and presentations from this course can be found in the course FTP.

 Presentation slides –  View or download the slides

 Recorded lectures – Watch the lecture videos 

 Practicals – View or download the slides, exercises, datasets, analysis scripts and results

Format	Subject	Trainer
	Planning the experiment
	Keynote: Single cell, Single nucleus and Spatial Transcriptomics of PSC	Tallulah Andrews
	Experimental design	Tallulah Andrews
	Wet-lab overview	Wendi Bacon
	Dry-lab overview	Wendi Bacon
	Processing data
	Raw reads to expression matrix	Jiawei Wang and Jinzheng Ren
	QC, pre-processing and normalisation	Iris Diana Yu, Yuyao Song, Hugo Tavares
	Single cell Expression Atlas and single cell data submission	Liora Vilmovsky
	Analysing data
	Designing your analysis	Tallulah Andrews
	Dimensionality reduction, clustering and annotation	Anna Vathrakokili Pournara
	Batch correction and data integration	Yuyao Song
	Spatial transcriptomics	Nadav Yayon
	Abundance and differential expression	Andrian Yang