Single-cell transcriptome-wide association studies (scTWAS) bring a more precise way of studying gene-trait associations. Traditional TWAS approaches often struggle with the complexity of cell-type heterogeneity, meaning it can be hard to tell which specific cell types are driving observed genetic associations. scTWAS solves this issue by analyzing genetic data at the single-cell level, helping researchers identify how specific genes behave in individual cell types.
As scTWAS research expands, it creates large amounts of data and knowledge, which brings a new challenge: How can scientists efficiently organize and access all this information? The scTWAS Atlas is a powerful new platform developed at the Chinese Academy of Sciences that is designed to collect, curate, and integrate scTWAS data into a user-friendly resource. It compiles over 2.7 million gene-trait associations across 34 traits, 30 cell types, 9 cell conditions, and more than 16,000 genes.
The platform offers several unique features to help researchers explore these connections. One standout feature is the interactive knowledge graph, which combines single-cell expression quantitative trait loci (sc-eQTL) data with scTWAS associations. This graph allows users to visualize multi-omics networks, helping them understand how genetic variants influence biological processes across different cell types.
Another key benefit of the scTWAS Atlas is its ability to compare data across multiple cell types. Researchers can uncover genes that have either cell-type-specific effects or those that act across many cell types, providing insights into how different cells contribute to complex traits and diseases. With easy-to-navigate search tools and data visualization, the platform simplifies access to critical information, enabling researchers to explore regulatory mechanisms more effectively.
The scTWAS Atlas offers a valuable resource for advancing human health research. By allowing scientists to study genetic associations at the cellular level, it opens new doors for understanding how specific cells and genes influence biological processes, disease development, and treatment responses. This platform promises to be an essential tool for future research, leading to breakthroughs in personalized medicine and disease prevention.
Availability – https://ngdc.cncb.ac.cn/sctwas/