Integrated plasma proteomic and single-cell immune signaling network signatures demarcate mild, moderate, and severe COVID-19. Feyaerts et al.

Published: 9 June 2022| Version 1 | DOI: 10.17632/xss9pdtc4f.1
Contributors:
Dorien Feyaerts,
Julien Hedou,
Joshua Gillard,
Han Chen,
Eileen Tsai,
Laura Peterson,
Kazuo Ando,
Monali Manohar,
Evan Do,
Gopal K.R. Dhondalay,
Jessica Fitzpatrick,
Maja Artandi,
Iris Chang,
Theo Snow,
R. Sharon Chinthrajah,
Christopher Warren,
Richard Wittman,
Justin Meyerowitz,
Edward Ganio,
Ina Stelzer,
Xiaoyuan Han,
Franck Verdonk,
Dyani Gaudilliere,
Nilanjan Mukherjee,
Amy Tsai,
Kristen Rumer,
Danielle Jacobsen,
Zachary Bjornson-Hooper,
Sizun Jiang,
Sergio Fragoso,
Sergio Valdés-Ferrer,
J. Daniel Kelly,
David Furman,
Nima Aghaeepour,
Martin Angst,
Scott Boyd,
Benjamin Pinsky,
Garry Nolan,
Kari Nadeau,
Brice Gaudilliere,
David McIlwain

Description

Supplemental files from manuscript "Integrated plasma proteomic and single-cell immune signaling network signatures demarcate mild, moderate, and severe COVID-19" by Feyaerts et al. Complete data repository will be made available on https://doi.org/10.5061/dryad.9cnp5hqmn (Dryad) once article DOI is known. The supplementary data files contain: SupplementalFileS1.xlsx: supplemental data file containing bootstrap selected features related to Figure 3-4 and Figure S7-11; comparison of severity correlation of plasma proteome features with Filbin et al. dataset related to Figure S6; and results of GAM model related to Figure S12. SupplementalFileS2.xlsx: mass cytometry antibody panel. Related to Figure 1 and Figure S1 and S2. SupplementalFileS3.xlsx: Correlation of sMERTK levels and available markers of monocyte activation (Spearman correlation). Related to Figure 4.

Files

Institutions

Stanford University School of Medicine

Categories

Immunology, Cell Signaling, COVID-19

License