Single-Cell Trajectory Inference for Detecting Transient Events in Biological Processes.

ABSTRACT: Transient surges in gene or protein expression often mark the key regulatory checkpoints that propel cells from one functional state to the next, yet they are easy to miss in sparse, noisy single‑cell omics data. We introduce scTransient, a trajectory‑inference pipeline integrated into our cloud‑based single‑cell analysis platform PSCS. scTransient transforms single‑cell expression profiles into continuous pseudotime signals and couples them with wavelet‑based signal processing to isolate short‑lived but biologically meaningful bursts of activity. After ordering cells with unsupervised graph trajectories or supervised psupertime, scTransient windows expression values along pseudotime, applies a continuous wavelet transform, and assigns every gene a Transient‑Event Score (TES)

SUBMITTER: Hutton A 

PROVIDER: S-EPMC12132349 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature