Multicellular factor analysis of single-cell data for a tissue-centric understanding of disease Article Swipe
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.5281/zenodo.7660312
· OA: W4393550749
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:<br> 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<br> 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<br> 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<br> 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
