On April 2025, the research group led by Young Investigator Guanlin Wang from the Institute of Metabolism and Integrative Biology (IMIB), Fudan University published a research article entitled “Optimized upstream analytical workflow for single-nucleus transcriptomics in main metabolic tissues” in Life Metabolism.

This study underlines the important role of a standardized workflow in enhancing data quality and analytical reliability in snRNA-seq of metabolic tissue by combining rigorous preprocessing, cell-type clustering and annotation, and robust integration methods. By providing an open-access tutorial website (https://metabomicslab.github.io/snRNAseq-analysis-workflow/) and a Snakemake pipeline, researchers aim to make these analytical tools more accessible to the broader research community. This will broaden the application of single nucleus transcriptomics in metabolic biology to elucidate cellular heterogeneities and tissue-specific mechanisms and lay a strong foundation for future precision medicine targeting cell-specific functions.

Link: https://doi.org/10.1093/lifemeta/loaf010