pairOT: Identifying similar cell types and states across single-cell transcriptomic studies#

Align cell annotations across two datasets through annotation-informed optimal transport.

Getting started#

Please refer to the documentation, in particular, the API documentation.

Installation#

For detailed installation instructions, please refer to the installation guide.

Tutorial#

Please take a look at the following tutorials for detailed examples on how to use pairOT:

Detailed explanation#

For a detailed tutorial, please see the in depth tutorial.

Speed up pairOT computations#

For details on how to speed up pairOT model fits and reduce compute requirements, see the reduce compute requirements tutorial

Basics of using pairOT#

import scanpy as sc
import pairot as pr

# 1. Preprocess input data
adata_query, adata_ref = pr.pp.preprocess_adatas(
    sc.read_h5ad("path/to/query.h5ad"),
    sc.read_h5ad("path/to/reference.h5ad"),
    n_top_genes=750,
    cell_type_column_adata1="cell_type_column_query",
    cell_type_column_adata2="cell_type_column_ref",
    sample_column_adata1="sequencing_sample_column_query",
    sample_column_adata2="sequencing_sample_column_ref",
)

# 2. Initialize pairOT model
dataset_map = pr.tl.DatasetMap(adata_query, adata_ref)
dataset_map.init_geom(batch_size=512, epsilon=0.05)
dataset_map.init_problem(tau_a=1.0, tau_b=1.0)

# 3. Fit pairOT model
dataset_map.solve()
mapping = dataset_map.compute_mapping()
distance = dataset_map.compute_distance()

# 4. Visualize results
pr.pl.mapping(mapping)  # similarity matrix
distance = distance.loc[
    mapping.max(axis=1).sort_values(ascending=False).index.tolist(),
    mapping.max().sort_values(ascending=False).index.tolist(),
]  # order cluster distance matrix the same way as similarity matrix
pr.pl.distance(distance)  # cluster distance matrix

Release notes#

See the changelog.

Contact#

If you found a bug, please use the issue tracker.

Citation#

t.b.a

References#

pairOT was written by Felix Fischer <felix.fischer@helmholtz-munich.de>

Support for software development, testing, modeling, and benchmarking provided by the Cell Annotation Platform team (Roman Mukhin)

pairOT: Identifying similar cell types and states across single-cell transcriptomic studies

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