Logo image
The Immune Signatures data resource, a compendium of systems vaccinology datasets
Journal article   Open access   Peer reviewed

The Immune Signatures data resource, a compendium of systems vaccinology datasets

Joann Diray-Arce, Helen E R Miller, Evan Henrich, Bram Gerritsen, Matthew P Mulè, Slim Fourati, Jeremy Gygi, Thomas Hagan, Lewis Tomalin, Dmitry Rychkov, …
Scientific data, v 9(1), pp 635-635
20 Oct 2022
PMID: 36266291
url
https://www.nature.com/articles/s41597-022-01714-7.pdfView
Published, Version of Record (VoR) Open
url
https://doi.org/10.1038/s41597-022-01714-7View
Published, Version of Record (VoR) Open

Abstract

Humans Systems Biology - methods Vaccines Vaccinology
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.

Metrics

4 Record Views
16 citations in Scopus

Details

UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#3 Good Health and Well-Being

InCites Highlights

Data related to this publication, from InCites Benchmarking & Analytics tool:

Collaboration types
Domestic collaboration
International collaboration
Web of Science research areas
Immunology
Logo image