moscot.problems.time.LineageProblem

class moscot.problems.time.LineageProblem(adata, **kwargs)

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

Methods

add_problem(key, problem, *[, overwrite])	Add a subproblem.
annotation_mapping(mapping_mode, ...[, ...])	Transfer annotations between distributions.
cell_transition(source, target, ...[, ...])	Aggregate the transport matrix.
compute_batch_distances(time, batch_key[, ...])	Compute the average Wasserstein distance between batches for a specific time point.
compute_entropy(source, target[, forward, ...])	Compute the conditional entropy per cell.
compute_feature_correlation(obs_key[, ...])	Compute correlation of push-forward or pull-back distribution with features.
compute_interpolated_distance(source, ...[, ...])
compute_random_distance(source, ...[, ...])
compute_time_point_distances(source, ...[, ...])
load(path)	Load the model from a file.
prepare(time_key[, lineage_attr, ...])	Prepare the lineage problem problem.
pull(source, target[, data, subset, ...])	Pull mass from target to source.
push(source, target[, data, subset, ...])	Push mass from source to target.
remove_problem(key)	Remove a subproblem.
sankey(source, target, source_groups, ...[, ...])	Compute a Sankey diagram between cells across time points.
save(path[, overwrite])	Save the problem to a file.
score_genes_for_marginals([...])	Compute gene scores to obtain prior knowledge about proliferation and apoptosis.
solve([alpha, epsilon, tau_a, tau_b, rank, ...])	Solve the lineage problem.

Attributes

adata	Annotated data object.
apoptosis_key	Key in obs where cell apoptosis is stored.
cell_costs_source	Cell cost obtained by the first dual potential.
cell_costs_target	Cell cost obtained by the second dual potential.
posterior_growth_rates	Posterior estimate of the source growth rates.
prior_growth_rates	Prior estimate of the source growth rates.
problem_kind	Kind of the underlying problem.
problems	OT subproblems that define the biological problem.
proliferation_key	Key in obs where cell proliferation is stored.
solutions	Solutions to the problems.
stage	Problem stage.
temporal_key	Temporal key in obs.

Parameters:

• adata (AnnData)

• kwargs (Any)