Skip to main content
Premium Trial:

Request an Annual Quote

Team Shares Marker Detection Method for Single-Cell Data

In Nucleic Acids Research, investigators in Germany outline a "single-cell marker identification by enrichment scoring," or SEMITONES, approach for finding informative markers in single-cell RNA sequence, single-cell ATAC-seq, or other single-cell omics datasets without a clustering assignment step. Along with analyses of simulated datasets, the team used the SEMITONES method to find cell identity insights from publicly available scRNA-seq and scATAC-seq data for human hematopoietic cells and through an analysis of published spatial transcriptomic data from the mouse brain. "The method allows for the identification of both local markers, i.e. features that are only detected in a small group of highly similar cells, and global markers, i.e. features that are detected in a larger group of cells covering several cell states," the authors write, noting that SEMITONES "qualitatively and quantitatively outperforms existing methods for the retrieval of cell identity markers from single-cell omics data."