Single-cell multi-omic profiling of glioblastoma-associated myeloid cells

This repository contains the code used to analyze the data in Antunes et al. Nature Neuroscience (2020). In this study, we mapped the glioblastoma immune landscape in newly diagnosed and recurrent patients and in mouse tumors via scRNA-seq and CITE-seq analysis. This revealed a large and diverse myeloid compartment, with dendritic cell and macrophage populations that were conserved across species and were dynamic across disease stages.

Code

• script_scRNAseq.R = script to analyse single cell RNA-seq data
• script_Citeseq.R = script to analyse CITE-Seq data

Webtool

Browse through all the data via our webtool: Brain Immune Atlas

Citation

If you use our data or code for your work please cite the following publication:

Ana Rita Pombo Antunes, Isabelle Scheyltjens, Francesca Lodi, Julie Messiaen, Asier Antoranz, Johnny Duerinck, Daliya Kancheva, Liesbet Martens, Karen De Vlaminck, Hannah Van Hove , Signe Schmidt Kjølner Hansen, Francesca Maria Bosisio, Koen Van der Borght, Steven De Vleeschouwer, Raf Sciot, Luc Bouwens, Michiel Verfaillie, Niels Vandamme, Roosmarijn E. Vandenbroucke, Olivier De Wever, Yvan Saeys, Martin Guilliams, Conny Gysemans, Bart Neyns, Frederik De Smet, Diether Lambrechts, Jo A. Van Ginderachter, Kiavash Movahedi. Single-cell multi-omic profiling of glioblastoma-associated myeloid cells across species and disease stage reveals macrophage competition and functional specialization. Nature Neuroscience. 2021 Apr;24(4):595-610. doi: 10.1038/s41593-020-00789-y. Epub 2021 Mar 29. PMID: 33782623

Primary contact:

Kiavash Movahedi, PhD

Professor
Laboratory for Molecular and Cellular Therapy\ Vrije Universiteit Brussel
Laarbeeklaan 103, Brussels Belgium
kiavash.movahedi@vub.be

Questions about the code:

Daliya Kancheva, PhD

daliya.kancheva@vub.be