A Review of AI Revolution in Transcriptomics:

From Single Cells to Spatial Atlases

Overview

This comprehensive review systematically organizes over 150 AI tools and methods applied to single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST). We categorize these approaches into a tri-partite framework encompassing Task-specific Methods, Foundation Models, and AI Agents. This website serves as a supplement to our published review, providing visual representations, detailed tables, and navigable access to all reviewed tools.

Key Contributions: We synthesize the evolution of AI methods in transcriptomics, highlighting the transition from specialized, interpretable task-specific approaches to scalable, generalizable foundation models and fully automated AI agents. Our analysis reveals complementary strengths and opportunities for synergistic combinations of these three paradigms.

Figure 1: Evolution of AI Methods in Transcriptomics

Timeline of AI Methods Evolution
Figure 1 Caption: In our review Artificial Intelligence Revolution in Transcriptomics: From Single Cells to Spatial Atlases, we systematically organized over 150 tools and reviewed these tools based on workflow in single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST), respectively. Furthermore, we categorized recent AI advanced paradigms—Foundation Models and AI Agents—into a tri-partite framework highlighting the evolution from specialized methods to general-purpose approaches.

Figure 2: AI Paradigm Framework for Transcriptomics

AI Paradigm Framework
Figure 2 Caption: We reviewed pros and cons of the three AI paradigm applications in Transcriptomics (scRNA-seq, ST), highlighting the future promising combination among them, which achieves general, interpretable and labor-saving performance. The framework shows how task-specific methods, foundation models, and AI agents complement each other in advancing transcriptomics research.

Explore the Full Review

📊 Task-specific Methods

Browse curated collections of specialized methods for scRNA-seq and spatial transcriptomics with detailed statistics and implementation information.

scRNA-seq Methods ST Methods

🚀 Advanced Paradigms

Discover foundation models and AI agents representing the cutting edge of transcriptomics analysis with scale and automation capabilities.

Foundation Models AI Agents

📌 About This Website

This website is primarily used for providing extra information about tools reviewed in our comprehensive survey. The main content is organized into Tables A, B, C, and D, which serve as the foundation for our analysis. View Table A (scRNA-seq Methods) | View Table B (ST Methods) | View Table C (Foundation Models) | View Table D (AI Agents)