Automated cell type annotation and exploration of single-cell signaling dynamics using mass cytometry

Automated cell type annotation and exploration of single-cell signaling dynamics using mass cytometry

Blog Article

Summary: Mass cytometry by time-of-flight (CyTOF) is an emerging technology allowing for in-depth characterization of cellular heterogeneity in cancer and other diseases.Unfortunately, high-dimensional analyses of CyTOF data remain quite demanding.Here, we deploy a bioinformatics framework that tackles two fundamental problems in CyTOF analyses namely (1) automated annotation of cell populations guided by a reference dataset and (2) systematic utilization 2023 volkl revolt 104 of single-cell data for effective patient stratification.

By applying this framework on several publicly available datasets, we demonstrate that the Scaffold approach achieves good trade-off between sensitivity and specificity for automated cell type annotation.Additionally, a case study focusing on a cohort of 43 leukemia patients reported salient interactions between signaling proteins that are sufficient to predict short-term survival at green snowflake japanese maple time of diagnosis using the XGBoost algorithm.Our work introduces an automated and versatile analysis framework for CyTOF data with many applications in future precision medicine projects.