Cytometry Masked Autoencoder: An Accurate and Interpretable Automated Immunophenotyper

High-throughput single-cell cytometry data are crucial for understanding involvement of immune system in diseases and responses to treatment. Traditional methods for annotating cytometry data, specifically manual gating and clustering, face challenges in scalability, robustness, and accuracy. In thi...

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Vydané v:	bioRxiv
Hlavní autori:	Kim, Jaesik, Ionita, Matei, Lee, Matthew, Mckeague, Michelle L, Ajinkya Pattekar, Painter, Mark M, Wagenaar, Joost, Truong, Van, Norton, Dylan T, Divij Mathew, Nam, Yonghyun, Apostolidis, Sokratis A, Clendenin, Cynthia, Orzechowski, Patryk, Sang-Hyuk Jung, Woerner, Jakob, Ittner, Caroline Ag, Turner, Alexandra P, Mika Esperanza, Dunn, Thomas G, Mangalmurti, Nilam S, Reilly, John P, Meyer, Nuala J, Calfee, Carolyn S, Liu, Kathleen D, Matthy, Michael A, Lamorna Brown Swigart, Burnham, Ellen L, Mckeehan, Jeffrey, Gandotra, Sheetal, Russel, Derek W, Gibbs, Kevin W, Thomas, Karl W, Barot, Harsh, Greenplate, Allison R, Wherry, E John, Kim, Dokyoon
Médium:	Paper
Jazyk:	English
Vydavateľské údaje:	Cold Spring Harbor Cold Spring Harbor Laboratory Press 27.02.2024 Cold Spring Harbor Laboratory
Vydanie:	1.2
Predmet:	Automation Bioinformatics COVID-19 Cytometry Gating Immune response Phenotypes Predictions Severe acute respiratory syndrome coronavirus 2
ISSN:	2692-8205, 2692-8205
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