Prediction of standard cell types and functional markers from textual descriptions of flow cytometry gating definitions using machine learning.
Journal:
Cytometry. Part B, Clinical cytometry
Published Date:
Mar 7, 2022
Abstract
BACKGROUND: A key step in clinical flow cytometry data analysis is gating, which involves the identification of cell populations. The process of gating produces a set of reportable results, which are typically described by gating definitions. The non-standardized, non-interpreted nature of gating definitions represents a hurdle for data interpretation and data sharing across and within organizations. Interpreting and standardizing gating definitions for subsequent analysis of gating results requires a curation effort from experts. Machine learning approaches have the potential to help in this process by predicting expert annotations associated with gating definitions.