The Immune Dictionary and Immune Response Enrichment Analysis Web Portal 9315

Abstract Description RNA sequencing (RNA-seq) is a powerful and widely used technique in immunology to extract insights from biological data. However, software tools for inferring cytokine activities based on RNA-seq data have been limited. To address this gap, we created a web application that hosts our Immune Dictionary, a compendium of single-cell transcriptomic profiles of over 17 cell types in response to each of 86 cytokines in mouse lymph nodes in vivo, and its companion software, Immune Response Enrichment Analysis (IREA), that allows assessment of cytokine activities and immune cell polarization from gene expression data. Our web application allows for exploratory visualization of cytokine stimulation response in each major immune cell type and is optimized for browsing perturbational single-cell RNA-sequencing data. Furthermore, researchers can easily enter a list of genes involved in an immune process, and the IREA web portal will provide the predictions of key cytokines driving the immune process within minutes. Recent updates to the web portal include accelerated graph displays, expanded network analysis, additional coverage of immunostimulatory agents such as chemokines, and comprehensive user instructions for each software functionality. The study highlights the power of big data in accelerating advancements in immunology and immunotherapies and provides a freely available software tool for the biomedical research community to investigate cytokine-mediated gene regulation. Funding Sources Harvard School of Dental Medicine start-up funds Topic Categories Computational and Systems Immunology (COMP)

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Publication Details

Journal
The Journal of Immunology
Published
2025-11-01
DOI
https://doi.org/10.1093/jimmun/vkaf283.2735
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
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article

The Immune Dictionary and Immune Response Enrichment Analysis Web Portal 9315

Ang Cui, Aileen Ma, Lawrence Wang, Jorge Eduardo Pérez Pérez et al.
The Journal of Immunology
Single-cell and spatial transcriptomics
article

The Immune Dictionary and Immune Response Enrichment Analysis Web Portal 9315

Ang Cui, Aileen Ma, Lawrence Wang, Jorge Eduardo Pérez Pérez, Nicholas Lai, Brianna S. Yao, Pooja Paresh Savla
article en

Abstract

Abstract Description RNA sequencing (RNA-seq) is a powerful and widely used technique in immunology to extract insights from biological data. However, software tools for inferring cytokine activities based on RNA-seq data have been limited. To address this gap, we created a web application that hosts our Immune Dictionary, a compendium of single-cell transcriptomic profiles of over 17 cell types in response to each of 86 cytokines in mouse lymph nodes in vivo, and its companion software, Immune Response Enrichment Analysis (IREA), that allows assessment of cytokine activities and immune cell polarization from gene expression data. Our web application allows for exploratory visualization of cytokine stimulation response in each major immune cell type and is optimized for browsing perturbational single-cell RNA-sequencing data. Furthermore, researchers can easily enter a list of genes involved in an immune process, and the IREA web portal will provide the predictions of key cytokines driving the immune process within minutes. Recent updates to the web portal include accelerated graph displays, expanded network analysis, additional coverage of immunostimulatory agents such as chemokines, and comprehensive user instructions for each software functionality. The study highlights the power of big data in accelerating advancements in immunology and immunotherapies and provides a freely available software tool for the biomedical research community to investigate cytokine-mediated gene regulation. Funding Sources Harvard School of Dental Medicine start-up funds Topic Categories Computational and Systems Immunology (COMP)

The Journal of ImmunologyVol. 214(Supplement_1)
Broad Institute (US), Harvard University (US), University of Southern Maine (US)
Openalex Percentile: Top 68%
Single-cell and spatial transcriptomics
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