COVID-19 severity correlates with airway epithelium-immune cell interactions identified by single-cell analysis
datasetposted on 21.07.2020, 11:46 by Robert Lorenz Chua, Soeren Lukassen, Saskia Trump, Bianca P. Hennig, Daniel Wendisch, Fabian Pott, Olivia Debnath, Loreen Thürmann, Florian Kurth, Maria Theresa Völker, Julia Kazmierski, Bernd Timmermann, Sven Twardziok, Stefan Schneider, Felix Machleidt, Holger Müller-Redetzky, Melanie Maier, Alexander Krannich, Sein Schmidt, Felix Balzer, Johannes Liebig, Jennifer Loske, Norbert Suttorp, Jürgen Eils, Naveed Ishaque, Uwe Gerd Liebert, Christof von Kalle, Andreas Hocke, Martin Witzenrath, Christine Goffinet, Christian Drosten, Sven Laudi, Irina Lehmann, Christian Conrad, Leif-Erik Sander, Roland Eils
Single-cell RNA-Seq of airway samples of COVID-19 patients and healthy controls
This dataset comprises single-cell RNA-Seq data of nasopharyngeal, protected specimen brush, and bronchial lavage samples of 19 COVID-19 patients (eight moderate and eleven critical according to the WHO classification) and five healthy controls, for a total of 36 samples.
An in-depth description is presented in the manuscript "Cross-talk between the airway epithelium and activated immune cells defines severity in COVID-19" (https://www.medrxiv.org/content/10.1101/2020.04.29.20084327v1).
The data is uploaded as two .rds files of Seurat objects that can be imported into R. The _main file contains all samples from the nasopharynx, while the _loc file contains data from nasopharyngeal, protected specimen brush, and bronchial lavage samples of two patients.
A quantification of viral RNA reads (as CPM, in total over cells and background) is provided as .xlsx file. Please note that these values may differ from viral load estimates obtained from diagnostic procedures and may be less accurate.
Raw count values (cellranger output) are provided in the file count_matrices_NBT.tar.