User API#

Import moscot as:

import moscot as mt

Biological Problems#

time.TemporalProblem(adata, **kwargs)

Class for analyzing time-series single cell data based on [Schiebinger et al., 2019].

time.LineageProblem(adata, **kwargs)

Estimator for modelling time series single cell data based on [Lange et al., 2023].

space.AlignmentProblem(adata, **kwargs)

Class for aligning spatial omics data, based on [Zeira et al., 2022].

space.MappingProblem(adata_sc, adata_sp)

Class for mapping single cell omics data onto spatial data, based on [Nitzan et al., 2019].

spatiotemporal.SpatioTemporalProblem(adata, ...)

Class for analyzing time series spatial single-cell data.

cross_modality.TranslationProblem(adata_src, ...)

Class for integrating single-cell multi-omics data, based on [Demetci et al., 2022].

Generic Problems#

generic.SinkhornProblem(adata, **kwargs)

Class for solving a linear problem.

generic.GWProblem(adata, **kwargs)

Class for solving the GW or FGW problems.

generic.FGWProblem(adata, **kwargs)

Class for solving the FGW problem.


plotting.cell_transition(obj[, key, ...])

Plot an aggregate cell transition matrix.

plotting.sankey(obj[, key, captions, title, ...])

Plot a Sankey diagram between cells across time points.

plotting.push(obj[, key, basis, ...])

Plot the push-forward distribution.

plotting.pull(obj[, key, basis, ...])

Plot the pull-back distribution.


datasets.bone_marrow([path, force_download])

Multiome data of bone marrow measurements [Luecken et al., 2021].

datasets.c_elegans([path, force_download])

scRNA-seq time-series dataset of C.elegans embryogenesis [Packer et al., 2019].

datasets.drosophila([path, force_download])

Embryo of Drosophila melanogaster described in [Li et al., 2022].

datasets.hspc([path, force_download])

CD34+ hematopoietic stem and progenitor cells from 4 healthy human donors.

datasets.mosta([path, force_download])

Preprocessed and extracted data as provided in [Chen et al., 2022].

datasets.sciplex([path, force_download])

Perturbation dataset published in [Srivatsan et al., 2020].

datasets.sim_align([path, force_download])

Spatial transcriptomics simulated dataset as described in [Jones et al., 2022].

datasets.simulate_data([n_distributions, ...])

Simulate data.

datasets.tedsim([path, force_download])

Dataset simulated with TedSim [Pan et al., 2022].

datasets.zebrafish([path, force_download])

Lineage-traced scRNA-seq time-series dataset of Zebrafish heart regeneration [Hu et al., 2022].