Accessible Tools and Interpretable Models for Uncovering Complex Biological Signals in Single-Cell Genomics Data

Music City Center 

Single-cell RNA sequencing (scRNA-seq) experiments have become instrumental in developmental and differentiation studies, enabling the profiling of cells at a single or multiple time-points to uncover subtle variations in expression profiles reflecting underlying biological processes. However, researchers encounter routine challenges in their analysis due to uncertainty with respect to selecting the most appropriate methods and parameters. Additionally, trajectory methods' performances are highly dataset-specific. We developed Escort, a novel framework for evaluating a dataset's suitability for trajectory inference and quantifying trajectory-specific properties influenced by analysis decisions. We demonstrate Escort's ability to both alleviate the decision burden inherent to trajectory inference analysis and in obtaining more accurate trajectories based on data-driven evaluations. Escort is implemented in an accessible R package and R/Shiny application, providing researchers with the necessary tools to make informed decisions during trajectory analysis and enabling new insights into dynamic biological processes at single-cell resolution.

trajectory analysis, biological processes, scRNA-seq, interactive software tools