Mon Feb 28, 2022 5:50 pm
2022-Hao et al-preprint
"Dictionary learning for integrative, multimodal, and scalable single-cell analysis"
Yuhan Hao, Tim Stuart, Madeline Kowalski, Saket Choudhary, Paul Hoffman, Austin Hartman, Avi Srivastava, Gesmira Molla, Shaista Madad, Carlos Fernandez-Granda, Rahul Satija
bioRxiv, posted February 26, 2022
https://doi.org/10.1101/2022.02.24.481684
- will update when/if this is peer-reviewed and published
- reuses 2021-COMBAT Consortium et al-preprint (2021-COMBAT Consortium et al-Cell)
"Human PBMC CyTOF dataset:
This human PBMC CyTOF dataset was generated by the COVID-19 Multi-omics Blood Atlas COMBAT
consortium, and consists of 7.11 million cells with a panel of 47 antibodies. We removed cells from sepsis
patients, yielding a remainder of 5.17 million cells. We use the normalized expression matrices as quantified
in the original study. As this dataset is used as a query dataset in this manuscript, we do not perform
unsupervised dimensionality reduction on the protein data.
Data acquisition source: https://zenodo.org/record/5139561"
Yuhan Hao, Tim Stuart, Madeline Kowalski, Saket Choudhary, Paul Hoffman, Austin Hartman, Avi Srivastava, Gesmira Molla, Shaista Madad, Carlos Fernandez-Granda, Rahul Satija
bioRxiv, posted February 26, 2022
https://doi.org/10.1101/2022.02.24.481684
- will update when/if this is peer-reviewed and published
- reuses 2021-COMBAT Consortium et al-preprint (2021-COMBAT Consortium et al-Cell)
"Human PBMC CyTOF dataset:
This human PBMC CyTOF dataset was generated by the COVID-19 Multi-omics Blood Atlas COMBAT
consortium, and consists of 7.11 million cells with a panel of 47 antibodies. We removed cells from sepsis
patients, yielding a remainder of 5.17 million cells. We use the normalized expression matrices as quantified
in the original study. As this dataset is used as a query dataset in this manuscript, we do not perform
unsupervised dimensionality reduction on the protein data.
Data acquisition source: https://zenodo.org/record/5139561"