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Mouse-Specific Single cell cytokine activity prediction and Estimation (MouSSE).

Azka Javaid1, H Robert Frost1

  • 1Department of Biomedical Data Science, Dartmouth College, Hanover, New Hampshire, United States of America.

Plos Computational Biology
|September 19, 2025
PubMed
Summary

We developed MouSSE, a new method for estimating cytokine activity at the single-cell level in mouse immune studies. MouSSE accurately predicts cytokine activity in murine single-cell RNA-sequencing and spatial transcriptomics data.

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Area of Science:

  • Immunology
  • Computational Biology
  • Genomics

Background:

  • Accurate cell-level cytokine activity characterization is crucial for understanding immune-mediated diseases.
  • Existing methods like SCAPE are designed for human data, necessitating a mouse-specific approach.

Purpose of the Study:

  • To introduce MouSSE, a novel computational method for estimating cell-level cytokine activity in murine single-cell RNA-sequencing (scRNA-seq) and spatial transcriptomics (ST) data.
  • To provide a robust tool for analyzing cytokine signaling in mouse models of disease.

Main Methods:

  • MouSSE utilizes a gene set scoring approach to estimate the activity of 86 distinct cytokines.
  • Cytokine-specific gene sets are derived from the Immune Dictionary, and scores are calculated using a modified Variance-adjusted Mahalanobis (VAM) technique.
  • The method incorporates positive and negative gene weights for enhanced accuracy.

Main Results:

  • MouSSE demonstrated superior performance compared to 10 other cytokine activity estimation methods in external validation datasets.
  • Stratified cross-validation using the Immune Dictionary confirmed MouSSE's accuracy and reliability.
  • The method effectively estimates cell-level cytokine activity in mouse scRNA-seq and ST data.

Conclusions:

  • MouSSE is a highly effective and validated method for cell-level cytokine activity estimation in murine transcriptomics data.
  • This tool will advance the study of immune responses and related diseases in mouse models.
  • An R package for MouSSE is available for public use.