RESEARCH USE
Where Monocle 3 fits
Create a cell_data_set from quality-controlled single-cell expression data, perform dimensionality reduction, clustering, and partitioning, then learn a principal graph and choose biologically justified root nodes for each partition before ordering cells in pseudotime. Preserve gene selection, batch handling, reduction settings, partitions, root choices, software version, and intermediate objects, and test whether the trajectory remains stable under other reasonable settings.
Research tasks
- Cluster and describe single-cell expression states
- Learn cell-state trajectories and order cells in pseudotime
- Test genes that vary along trajectories or between states
What to evaluate before use
- Pseudotime is relative progress along a learned graph, not elapsed time. Branches and direction depend on the input, reduction, partitions, and selected roots.
- A trajectory inferred from cross-sectional expression data does not by itself establish lineage or cell-fate decisions. Important claims require time-resolved, lineage-tracing, or other experimental evidence.
Verification note
This entry summarizes the resource's role without assessing scientific accuracy or endorsing its outputs. Features and terms can change; consult the official source before adopting it for consequential work.
Last verified: 2026-09-18
Source: official documentation ↗