monocle3-python
Python port of the R monocle3 single-cell trajectory toolkit.
The port keeps monocle3's orchestration and R-side numerical behaviour while replacing the cell_data_set S4 container with anndata.AnnData and delegating non-monocle-specific algorithms to the scverse ecosystem (umap-learn, openTSNE, leidenalg, statsmodels, …).
Installation
pip install monocle3-python # from PyPI
For local development:
git clone https://github.com/Bio-Babel/Monocle3-python.git
cd Monocle3-python
pip install -e ".[dev]"
Quickstart
import monocle3 as m3
adata = m3.load_packer_embryo() # AnnData (6188 × 20222)
m3.preprocess_cds(adata, num_dim=50) # size-factor norm + truncated PCA
m3.align_cds(adata, alignment_group="batch")
m3.reduce_dimension(adata) # UMAP via umap-learn
m3.cluster_cells(adata) # Leiden
m3.learn_graph(adata) # SimplePPT principal graph
m3.order_cells(adata, root_pr_nodes=["Y_1"]) # pseudotime
m3.plot_cells(adata, color_cells_by="pseudotime")
Tutorials
Runnable notebooks that reproduce the R monocle3 vignettes live under tutorials/:
| Notebook | Dataset |
|---|---|
c_elegans_embryo_v2.ipynb |
Packer et al. 2019 — C. elegans embryo trajectory |
c_elegans_L2_v2.ipynb |
Cao et al. 2017 — C. elegans L2 clustering + Garnett markers |
License
Artistic-2.0, matching the upstream R monocle3.
1 maintainer
Release files for monocle3-python 1.4.26.post1
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