The Immune Signatures data resource, a compendium of systems vaccinology datasets
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Published:2022-10-20
Issue:1
Volume:9
Page:
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ISSN:2052-4463
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Container-title:Scientific Data
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language:en
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Short-container-title:Sci Data
Author:
Diray-Arce Joann, Miller Helen E. R., Henrich Evan, Gerritsen BramORCID, Mulè Matthew P., Fourati SlimORCID, Gygi Jeremy, Hagan ThomasORCID, Tomalin LewisORCID, Rychkov Dmitry, Kazmin Dmitri, Chawla Daniel G., Meng Hailong, Dunn PatrickORCID, Campbell John, Deckhut-Augustine Alison, Gottardo Raphael, Haddad Elias K., Hafler David A., Harris Eva, Farber Donna, Levy Ofer, McElrath Julie, Montgomery Ruth R., Peters Bjoern, Rahman Adeeb, Reed Elaine F., Rouphael Nadine, Fernandez-Sesma Ana, Sette Alessandro, Stuart Ken, Togias Alkis, Tsang John S., Sarwal Minnie, Tsang John S.ORCID, Levy OferORCID, Pulendran BaliORCID, Sekaly Rafick, Floratos Aris, Gottardo RaphaelORCID, Kleinstein Steven H.ORCID, Suárez-Fariñas MayteORCID,
Abstract
AbstractVaccines are among the most cost-effective public health interventions for preventing infection-induced morbidity and mortality, yet much remains to be learned regarding the mechanisms by which vaccines protect. Systems immunology combines traditional immunology with modern ‘omic profiling techniques and computational modeling to promote rapid and transformative advances in vaccinology and vaccine discovery. The NIH/NIAID Human Immunology Project Consortium (HIPC) has leveraged systems immunology approaches to identify molecular signatures associated with the immunogenicity of many vaccines. However, comparative analyses have been limited by the distributed nature of some data, potential batch effects across studies, and the absence of multiple relevant studies from non-HIPC groups in ImmPort. To support comparative analyses across different vaccines, we have created the Immune Signatures Data Resource, a compendium of standardized systems vaccinology datasets. This data resource is available through ImmuneSpace, along with code to reproduce the processing and batch normalization starting from the underlying study data in ImmPort and the Gene Expression Omnibus (GEO). The current release comprises 1405 participants from 53 cohorts profiling the response to 24 different vaccines. This novel systems vaccinology data release represents a valuable resource for comparative and meta-analyses that will accelerate our understanding of mechanisms underlying vaccine responses.
Funder
U.S. Department of Health & Human Services | NIH | National Institute of Allergy and Infectious Diseases Division of Intramural Research, National Institute of Allergy and Infectious Diseases
Publisher
Springer Science and Business Media LLC
Subject
Library and Information Sciences,Statistics, Probability and Uncertainty,Computer Science Applications,Education,Information Systems,Statistics and Probability
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