FLASH-seq analysis of adipocyte precursor subpopulations (P1 and P2) isolated from a high-fat diet (HFD) mouse, comparing two sorting strategies: conventional manual gating and ConvexGating
This experiment evaluates whether the gates predicted by the tool ConvexGating improve the isolation of adipocyte precursor subpopulations (P1 and P2) from one high-fat diet (HFD) mouse relative to conventional manual gating. Visceral white adipose tissue (WAT) was chosen as a challenging test case for algorithm transfer beyond immune cells, given its high lipid content and cellular fragility, which complicate accurate cell sorting. WAT cells were stained and sorted into P1 and P2 subpopulations, then subjected to plate-based single-cell RNA sequencing via FLASH-Seq to confirm subpopulation identity. By directly comparing the two gating strategies, we assessed whether ConvexGating yields superior population purity, robustness, and transcriptional resolution - and whether algorithm-guided gating more reliably captures functionally distinct adipocyte precursor states to enhance downstream transcriptomic profiling and biological interpretability.
This experiment evaluates whether the gates predicted by the tool ConvexGating improve the isolation of adipocyte precursor subpopulations (P1 and P2) from one high-fat diet (HFD) mouse relative to conventional manual gating. Visceral white adipose tissue (WAT) was chosen as a challenging test case for algorithm transfer beyond immune cells, given its high lipid content and cellular fragility, which complicate accurate cell sorting. WAT cells were stained and sorted into P1 and P2 subpopulations, then subjected to plate-based single-cell RNA sequencing via FLASH-Seq to confirm subpopulation identity. By directly comparing the two gating strategies, we assessed whether ConvexGating yields superior population purity, robustness, and transcriptional resolution - and whether algorithm-guided gating more reliably captures functionally distinct adipocyte precursor states to enhance downstream transcriptomic profiling and biological interpretability.
European Bioinformatics Institute