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 sources iphone 90m 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 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 time of diagnosis using the XGBoost algorithm.Our work introduces an automated and versatile analysis framework for CyTOF data with many applications in sony c future precision medicine projects.