Trajectory Inference for Unraveling Dynamic Biological Processes from Raman Spectral Data.

ABSTRACT

Cell heterogeneity is a crucial parameter for understanding the complexity of numerous biomedical issues. Trajectory inference-based approaches are recent tools developed for single-cell transcriptomics (scRNA-seq) data analysis. They aim to reconstruct evolving pathways from the variety of cell states that coexist simultaneously in a cell population. We propose to expand this concept to Raman spectroscopy, a label-free modality that probes the global molecular nature of a sample, by investigating the dynamics of adipocyte differentiation.