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Related Experiment Video

Updated: Jul 8, 2026

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

scImmuneCo: a compendium of cell-type-specific functional modules for decoding immune responses from single-cell

Frank Qingyun Wang¹, Caicai Zhang¹, Xiao Dang¹

¹Department of Paediatrics and Adolescent Medicine, The University of Hong Kong, 21 Sassoon Road, Pokfulam, Hong Kong, 999077, China.

Briefings in Bioinformatics

|July 7, 2026

Summary

scImmuneCo provides cell-specific gene modules from single-cell RNA sequencing data to reveal immune response details. This resource clarifies immune cell functions and disease mechanisms with high resolution.

Keywords:

cellular resolution immune response scRNA-seq transcriptional program

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Mapping Infant Immunity with Minimal Input: Integrative Single-Cell and Multiomic Profiling

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Last Updated: Jul 8, 2026

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

Mapping Infant Immunity with Minimal Input: Integrative Single-Cell and Multiomic Profiling

Mapping Infant Immunity with Minimal Input: Integrative Single-Cell and Multiomic Profiling

Published on: April 3, 2026

Area of Science:

Immunology
Computational Biology
Genomics

Background:

Traditional methods struggle to capture immune response heterogeneity.
Single-cell RNA sequencing (scRNA-seq) offers higher resolution for immune studies.

Purpose of the Study:

To develop a resource for cell-specific immune co-expression modules.
To enable high-resolution functional inference of immune mechanisms.

Main Methods:

Constructed 873 immune cell-specific co-expression modules using a graph-based framework.
Analyzed scRNA-seq data from 1.78 million cells across 17 immunological conditions.
Integrated an R package and web portal for data accessibility.

Main Results:

Identified 20 interferon-related modules, revealing conserved and cell-type-specific programs.
Uncovered age-associated CD8+ T cell programs, showing shifts in translation and cytotoxicity.
Demonstrated cell-type-specific differences in immune responses, missed by traditional pathway analysis.

Conclusions:

scImmuneCo enhances understanding of immune mechanisms and disease processes at cellular resolution.
The resource facilitates data-driven functional inference for immunological research.
Provides a scalable framework for dissecting transcriptional programs in immune cells.