# RNAPaceDB: a dedicated database to dissect RNA velocity across diverse cell types

## TL;DR

RNAPaceDB is a database that helps researchers study RNA velocity across different cell types and diseases to understand gene expression dynamics and discover new biomarkers.

## Contribution

RNAPaceDB is a novel database integrating RNA velocity data from over 2.1 million cells across 81 cell types and 41 diseases.

## Key findings

- RNAPaceDB integrates data from 144 datasets and provides 4380 velocity stream plots from six models.
- The database enables exploration of RNA velocity profiles for over 18,000 genes across cell development processes.
- It offers tools to analyze cell cluster distribution, development trajectories, and differential velocity genes.

## Abstract

RNA velocity, which reflects the balance between nascent RNA synthesis and mature RNA degradation, provides a kinetic perspective to explore gene expression dynamics and cellular state transitions, offering profound insights into diverse biological processes and disease mechanisms. Deciphering RNA velocity patterns across cell types and contexts will deepen our understanding of the temporal logic of gene regulation and facilitating the discovery of novel biomarkers and therapeutic targets. Here, we present RNAPaceDB (http://biocclab.cn/RNAPaceDB/), a dedicated database to dissect RNA velocity across diverse cell types. RNAPaceDB integrates single-cell RNA sequencing profiles from 144 datasets, encompassing over 2.1 million cells across 81 cell types and 41 diseases, and offers 4380 velocity stream plots derived from six computational models. Using RNAPaceDB, users can explore RNA velocity profiles of >18 000 genes across cell development processes. Additionally, RNAPaceDB provides integrated online interfaces to retrieve and analyze cell cluster distribution, cell development trajectories, cell type-specific differential velocity genes, and functional enrichments under varying conditions. Collectively, RNAPaceDB serves as a valuable resource for deciphering the temporal logic of gene expression dynamics, facilitating discoveries of regulatory mechanisms, biomarkers, and therapeutic targets in precision medicine and systems biology.

Graphical Abstract