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Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

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Gateway analysis reveals transient molecular programs at cell-fate transitions.

Hu Cang¹, Sha Sun¹

¹Department of Developmental and Cell Biology, University of California, Irvine, Irvine, CA 92697, USA.

Biorxiv : the Preprint Server for Biology

|March 27, 2026

Summary

Gateway analysis identifies rare transition cells in single-cell atlases. This method reveals transient gene programs missed by standard methods, advancing cell fate research.

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Area of Science:

Computational Biology
Genomics
Developmental Biology

Background:

Single-cell atlases offer insights into cell identity but struggle to resolve rare, transient cell states during cell fate transitions.
Identifying molecular programs driving lineage changes is challenging due to the low abundance of these intermediate cells.

Purpose of the Study:

To develop a computational framework, gateway analysis, for identifying rare cell populations at fate boundaries.
To pinpoint specific genes (bell and valley genes) that characterize these transient cell states.

Main Methods:

Gateway analysis defines cell neighborhoods using binary mutual information (BMI) from gene expression patterns.
A regularized latent model preserves neighborhood structure to identify boundary cells.
The framework was applied to four diverse single-cell datasets.

Main Results:

Gateway analysis successfully identified rare boundary populations and their associated transient gene expression programs across reprogramming, gastrulation, pancreatic endocrinogenesis, and kidney injury datasets.
Key biological processes like epithelial remodeling, gastrulation regulation, endocrine differentiation signaling, and proteostasis were identified at specific transition points.
These transition signals were not detected by standard comparisons of stable cell populations.

Conclusions:

Gateway analysis provides a robust method for detecting rare transition-state cells and their defining molecular signatures in large single-cell atlases.
This framework enhances the understanding of dynamic cellular processes and cell fate decisions.
The identified bell and valley genes offer novel insights into the mechanisms governing cell transitions.