| Literature DB >> 36266291 |
Joann Diray-Arce1,2,3, Helen E R Miller4,5, Evan Henrich4,5, Steven H Kleinstein6, Mayte Suárez-Fariñas7,8, Bram Gerritsen6, Matthew P Mulè9,10, Slim Fourati11, Jeremy Gygi12, Thomas Hagan13,14,15, Lewis Tomalin16, Dmitry Rychkov17, Dmitri Kazmin18, Daniel G Chawla12, Hailong Meng6, Patrick Dunn19, John Campbell19, Minnie Sarwal17, John S Tsang9, Ofer Levy20,4,5,21, Bali Pulendran13, Rafick Sekaly11, Aris Floratos22, Raphael Gottardo4,5,23.
Abstract
Vaccines 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.Entities:
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Year: 2022 PMID: 36266291 PMCID: PMC9584267 DOI: 10.1038/s41597-022-01714-7
Source DB: PubMed Journal: Sci Data ISSN: 2052-4463 Impact factor: 8.501