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references.bib
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@article{Wolf2018,
author = {Wolf, F. Alexander
and Angerer, Philipp
and Theis, Fabian J.},
title = {SCANPY: large-scale single-cell gene expression data analysis},
journal = {Genome Biology},
year = {2018},
month = {Feb},
day = {06},
volume = {19},
number = {1},
pages = {15},
abstract = {Scanpy is a scalable toolkit for analyzing single-cell gene expression data. It includes methods for preprocessing, visualization, clustering, pseudotime and trajectory inference, differential expression testing, and simulation of gene regulatory networks. Its Python-based implementation efficiently deals with data sets of more than one million cells (https://github.com/theislab/Scanpy). Along with Scanpy, we present AnnData, a generic class for handling annotated data matrices (https://github.com/theislab/anndata).},
issn = {1474-760X},
doi = {10.1186/s13059-017-1382-0},
url = {https://doi.org/10.1186/s13059-017-1382-0}
}
@article {Marconato2023.05.05.539647,
author = {Luca Marconato and Giovanni Palla and Kevin A. Yamauchi and Isaac Virshup and Elyas Heidari and Tim Treis and Marcella Toth and Rahul B. Shrestha and Harald V{\"o}hringer and Wolfgang Huber and Moritz Gerstung and Josh Moore and Fabian J. Theis and Oliver Stegle},
title = {SpatialData: an open and universal data framework for spatial omics},
elocation-id = {2023.05.05.539647},
year = {2023},
doi = {10.1101/2023.05.05.539647},
publisher = {Cold Spring Harbor Laboratory},
abstract = {Spatially resolved omics technologies are transforming our understanding of biological tissues. However, handling uni- and multi-modal spatial omics datasets remains a challenge owing to large volumes of data, heterogeneous data types and the lack of unified spatially-aware data structures. Here, we introduce SpatialData, a framework that establishes a unified and extensible multi-platform file-format, lazy representation of larger-than-memory data, transformations, and alignment to common coordinate systems. SpatialData facilitates spatial annotations and cross-modal aggregation and analysis, the utility of which is illustrated via multiple vignettes, including integrative analysis on a multi-modal Xenium and Visium breast cancer study.Competing Interest StatementJ.M. holds equity in Glencoe Software which builds products based on OME-NGFF. F.J.T. consults for Immunai Inc., Singularity Bio B.V., CytoReason Ltd, Cellarity, and Omniscope Ltd, and has ownership interest in Dermagnostix GmbH and Cellarity.},
URL = {https://www.biorxiv.org/content/early/2023/05/08/2023.05.05.539647},
eprint = {https://www.biorxiv.org/content/early/2023/05/08/2023.05.05.539647.full.pdf},
journal = {bioRxiv}
}
@article{marconatoSpatialDataOpenUniversal2024,
title = {{{SpatialData}}: An Open and Universal Data Framework for Spatial Omics},
author = {Marconato, Luca and Palla, Giovanni and Yamauchi, Kevin A. and Virshup, Isaac and Heidari, Elyas and Treis, Tim and Vierdag, Wouter-Michiel and Toth, Marcella and Stockhaus, Sonja and Shrestha, Rahul B. and Rombaut, Benjamin and Pollaris, Lotte and Lehner, Laurens and V{\"o}hringer, Harald and Kats, Ilia and Saeys, Yvan and Saka, Sinem K. and Huber, Wolfgang and Gerstung, Moritz and Moore, Josh and Theis, Fabian J. and Stegle, Oliver},
year = {2024},
month = mar,
journal = {Nature Methods},
issn = {1548-7105},
doi = {10.1038/s41592-024-02212-x},
abstract = {Spatially resolved omics technologies are transforming our understanding of biological tissues. However, the handling of uni- and multimodal spatial omics datasets remains a challenge owing to large data volumes, heterogeneity of data types and the lack of flexible, spatially aware data structures. Here we introduce SpatialData, a framework that establishes a unified and extensible multiplatform file-format, lazy representation of larger-than-memory data, transformations and alignment to common coordinate systems. SpatialData facilitates spatial annotations and cross-modal aggregation and analysis, the utility of which is illustrated in the context of multiple vignettes, including integrative analysis on a multimodal Xenium and Visium breast cancer study.}
}