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2022-Saddawi-Konefka et al-preprint

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mleipold

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Posts: 5796

Joined: Fri Nov 01, 2013 5:30 pm

Location: Stanford HIMC, CA, USA

Post Fri Feb 04, 2022 4:44 pm

2022-Saddawi-Konefka et al-preprint

"Lymphatic-Preserving Treatment Sequencing with Immune Checkpoint Inhibition Unleashes cDC1-Dependent Antitumor Immunity in HNSCC"
Robert Saddawi-Konefka, Aoife O'Farrell, Farhoud Faraji, Lauren Clubb, Michael M Allevato, Nana-Ama A S Anang, Shawn M Jensen, Zhiyong Wang, Victoria H Wu, Bryan S Yung, Riyam Al Msari, Ida Franiak Pietryga, Alfredo A Molinolo, Jill P Mesirov, Aaron B Simon, Bernard A Fox, Jack D Bui, Andrew Sharabi, Ezra E W Cohen, Joseph A Califano, J Silvio Gutkind
bioRxiv, posted February 03, 2022
https://doi.org/10.1101/2022.02.01.478744

- will update when/if this is peer-reviewed and published

- "Data and materials availability: All data are available in the main text or the supplementary materials or will otherwise be made available on appropriate open-access platforms prior to the publication of this paper."
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mleipold

Guru

Posts: 5796

Joined: Fri Nov 01, 2013 5:30 pm

Location: Stanford HIMC, CA, USA

Post Mon Aug 08, 2022 3:11 pm

Re: 2022-Saddawi-Konefka et al-preprint

Now published:

Nat Commun. 2022, 13, 4298
https://doi.org/10.1038/s41467-022-31941-w

- still no CyTOF dataset accession given
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sgranjeaud

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Posts: 123

Joined: Wed Dec 21, 2016 9:22 pm

Location: Marseille, France

Post Tue Aug 16, 2022 3:29 pm

Re: 2022-Saddawi-Konefka et al-preprint

To detect clusters of cells with a similar expression of surface markers in CyTOF, single cells were gated and clustered using unsupervised dimensionality reduction algorithm optimal t-Distributed Stochastic Neighbor Embedding (opt-SNE) algorithm in OMIQ data analysis software 2022 (http://www.omiq.ai), 530 iterations, Perplexity 30, and Theta 0.5.

Unsupervised dimensionality reduction is not a clustering algorithm. Clustering algorithm provides each cell with a cluster assignment (ie an integer identifier). Unsupervised dimensionality reduction provides two new synthetic coordinates for each cell. Thus the cells represented the resulting 2D map could only be colored with a unique and same color. Alternatively, a coloring scale could show the density of cells on this 2D map. It's only the brain who groups the cells of the 2D map... or a clustering algorithm. When such confusion will end?

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