omicverse-single-cell-monocle2-trajectory
OmicVerse Single-Cell — Monocle2 Trajectory
Goal
Take a preprocessed annotated single-cell AnnData (typically myeloid / hematopoietic lineage) and fit a Monocle2-style trajectory: DDRTree-based ordering, pseudotime computation, branch-point detection, per-gene differential testing along pseudotime, and BEAM (Branch Expression Analysis Modeling) for branch-dependent genes. Visualise the result with the OmicVerse plotting stack (branch_streamplot, dynamic_heatmap, dynamic_trends) on top of the unified dynamic_features GAM-fitting backend.
Monocle here is a wrapper around the original Monocle2 logic re-implemented in Python; it operates on AnnData rather than cell_data_set and integrates with the rest of OmicVerse plotting / trajectory tooling. dynamic_features is the shared GAM backend used by every trajectory skill (Palantir, Slingshot, Monocle, etc.) so genes-along-pseudotime visualisations are interoperable.