Multicellular factor analysis of single-cell data for a tissue-centric understanding of disease
Creators
- 1. Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Bioquant, Heidelberg, Germany
- 2. Division of Computational Genomics and Systems Genetics, German Cancer Research Center (DKFZ), Heidelberg, Germany
Description
Collection of auxiliary data to reproduce the results from "Multicellular factor analysis of single-cell data for a tissue-centric understanding of disease".
Source code is available at: https://github.com/saezlab/MOFAcell
Exceptions: Spatial data is excluded
This folder contains processed data of the following publications, when using the data cite accordingly:
1) Kuppe C, Ramirez Flores RO, Li Z, Hayat S, Levinson RT, Liao X, Hannani MT, Tanevski J, Wünnemann F, Nagai JS, et al (2022) Spatial multi-omic map of human myocardial infarction. Nature 608: 766–777
2) Ramirez Flores RO, Lanzer JD, Holland CH, Leuschner F, Most P, Schultz J-H, Levinson RT & Saez-Rodriguez J (2021) Consensus Transcriptional Landscape of Human End-Stage Heart Failure. J Am Heart Assoc 10: e019667
3) Reichart D, Lindberg EL, Maatz H, Miranda AMA, Viveiros A, Shvetsov N, Gärtner A, Nadelmann ER, Lee M, Kanemaru K, et al (2022) Pathogenic variants damage cell composition and single cell transcription in cardiomyopathies. Science 377: eabo1984
4) Chaffin M, Papangeli I, Simonson B, Akkad A-D, Hill MC, Arduini A, Fleming SJ, Melanson M, Hayat S, Kost-Alimova M, et al (2022) Single-nucleus profiling of human dilated and hypertrophic cardiomyopathy. Nature 608: 174–180
Notes
Files
pub_data.zip
Files
(6.9 GB)
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