omicverse.single.Monocle

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omicverse.single.Monocle#

omicverse.single.Monocle(adata: AnnData)[source]#

Monocle2-style single-cell trajectory analysis.

Wraps a pure-Python implementation of Monocle 2 as a stateful analyzer operating on an AnnData object. All results are stored in the AnnData (.obs, .var, .uns['monocle'], .obsm) so the usual scanpy workflow continues to work seamlessly.

Parameters:

adata (AnnData) – Annotated data matrix (cells × genes). Expression matrix in adata.X should be raw/normalized counts (negative binomial model).

omicverse.single.adata#

The annotated data matrix with analysis results stored in-place.

Type:

AnnData

Examples

Basic trajectory analysis:

>>> mono = ov.single.Monocle(adata)
>>> mono.preprocess()              # size factors + dispersions
>>> mono.select_ordering_genes()   # high-variance gene selection
>>> mono.reduce_dimension()        # DDRTree
>>> mono.order_cells()             # assign pseudotime + State
>>> mono.plot_trajectory(color_by='clusters')
>>> mono.plot_genes_in_pseudotime(['Ins1', 'Gcg'])

Differential expression along pseudotime:

>>> de = mono.differential_gene_test()
>>> beam = mono.BEAM(branch_point=1)
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