Abstract
AbstractTransferring annotations of single-cell-, spatial- and multi-omics data is often challenging owing both to technical limitations, such as low spatial resolution or high dropout fraction, and to biological variations, such as continuous spectra of cell states. Based on the concept that these data are often best described as continuous mixtures of cells or molecules, we present a computational framework for the transfer of annotations to cells and their combinations (TACCO), which consists of an optimal transport model extended with different wrappers to annotate a wide variety of data. We apply TACCO to identify cell types and states, decipher spatiomolecular tissue structure at the cell and molecular level and resolve differentiation trajectories using synthetic and biological datasets. While matching or exceeding the accuracy of specialized tools for the individual tasks, TACCO reduces the computational requirements by up to an order of magnitude and scales to larger datasets (for example, considering the runtime of annotation transfer for 1 M simulated dropout observations).
Funder
Deutsche Forschungsgemeinschaft
Center for Interdisciplinary Data Science Research at the Hebrew University of Jerusalem
Human Frontier Science Program
U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute
U.S. Department of Health & Human Services | NIH | National Cancer Institute
U.S. Department of Health & Human Services | NIH | Office of Extramural Research, National Institutes of Health
U.S. Department of Health & Human Services | NIH | National Institute of Diabetes and Digestive and Kidney Diseases
Howard Hughes Medical Institute
Klarman Cell Observatory MIT Ludwig Center Manton Family Foundation
Israel Science Foundation
Azrieli Foundation
Google
Center for Interdisciplinary Data Science Research at the Hebrew University of Jerusalem Horizon Europe ERC Grant
Publisher
Springer Science and Business Media LLC
Subject
Biomedical Engineering,Molecular Medicine,Applied Microbiology and Biotechnology,Bioengineering,Biotechnology
Cited by
18 articles.
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