Systematic evaluation of tools used for single-cell m⁶A identification

N6-methyladenosine (m⁶A) modifications are prevalent across all mammals and represent the most abundant type of epigenetic modification. With advancements in research, new methods for single-cell m⁶A modification sequencing and prediction have continuously emerged. These methods provide researchers with powerful tools to explore the landscape of epigenetic modifications at the single-cell level. However, challenges such as operational complexity, limited sensitivity, resolution, and consistency across different techniques remain major obstacles for researchers in this field. In this study, we compared four representative single-cell m⁶A sequencing and prediction methods based on different principles. We also developed a single-cell m⁶A database, which is freely accessible online. The database allows users to search for the localization and modification levels of single-cell m⁶A modifications in human and mouse species on the basis of these methods. It also offers cell definitions, data visualization, and data download options. Additionally, we applied Scm⁶A to single-cell transcriptome data across cancers and spatial transcriptome data from UCEC to predict and visualize m⁶A modifications, demonstrating its unique superior performance.