science 🔬 New algorithm simplifies gene tracking in single-cell data
A new computational method called scLS was developed to analyze gene expression trajectories from scRNA-seq data. Researchers from Waseda University in Japan introduced scLS to handle complex cellular data sets. The study was made public on July 16, 2026, and published in Nucleic Acids Research on July 22, 2026. scLS uses the Lomb–Scargle periodogram to analyze irregularly sampled and branching trajectories without explicit regression models. This tool supports both dynamic and shifted gene expression tests, offering an efficient screening method. 🧬