Published April 13, 2020
| Version 1.0
Dataset
Open
Transcriptomic response of human cells to SARS-CoV-2, RSV and H1N1 (STAR + StringTie)
- 1. Center for Neurogenetics, Weill Cornell Medicine, Cornell University, New York, NY, USA
- 2. University of Lyon, INSA-Lyon, INRA, BF2I, Villeurbanne, France
- 3. Centre for Molecular Bioinformatics, Department of Biology, University Of Rome Tor Vergata, Rome, Italy
- 4. Centro de Investigacion Biomedica en Red de Enfermedades Raras, Universitat Pompeu Fabra, Spain
Description
These data represent results from:
- Processing reads from 20 experiments (part of GSE147507) by following a standard approach, which includes using STAR to align the reads to GRCh38 and StringTie to calculate the (raw) counts per experiment. These results depict the transcriptomic response of human cells to SARS-CoV-2, RSV and H1N1, and enrichment analyses based on genes differentially expressed in SARS-CoV-2 but not in RSV or H1N1. (Authors: V.A.-P., M.G.F. and A.G.)
- Aligning to SARS-CoV-2 and quantifying reads by using HISAT2 and StringTie. (Author: C.R.-A.)
Disclaimer: These results were obtained during the virtual BioHackathon 2020. As such, they are subject to ongoing research and have thus NOT yet undergone any scientific peer-review. That is, none of the contents can be considered to be free of errors and must be taken with caution!
Notes
Data uploaded here are licensed under the CC0 1.0 Universal license
Files
P1-GSE147507-Counts_by_gene.csv
Files
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Additional details
Related works
- Is supplement to
- Dataset: 10.5281/zenodo.3748026 (DOI)
References
- Ferrarini, Aguiar-Pulido et al. (2020). Global analysis of human SARS-CoV-2 infection and host-virus interaction. BioHackrXiv. https://doi.org/10.37044/osf.io/b4zkp