Fischer DS, Dony L, Konig M, Moeed A, Zappia L, Heumos L, Tritschler S, Holmberg O, Aliee H, Theis FJ (2021)
Publication Type: Journal article
Publication year: 2021
Book Volume: 22
Article Number: 248
Journal Issue: 1
DOI: 10.1186/s13059-021-02452-6
Single-cell RNA-seq datasets are often first analyzed independently without harnessing model fits from previous studies, and are then contextualized with public data sets, requiring time-consuming data wrangling. We address these issues with sfaira, a single-cell data zoo for public data sets paired with a model zoo for executable pre-trained models. The data zoo is designed to facilitate contribution of data sets using ontologies for metadata. We propose an adaption of cross-entropy loss for cell type classification tailored to datasets annotated at different levels of coarseness. We demonstrate the utility of sfaira by training models across anatomic data partitions on 8 million cells.
APA:
Fischer, D.S., Dony, L., Konig, M., Moeed, A., Zappia, L., Heumos, L.,... Theis, F.J. (2021). Sfaira accelerates data and model reuse in single cell genomics. Genome Biology, 22(1). https://doi.org/10.1186/s13059-021-02452-6
MLA:
Fischer, David S., et al. "Sfaira accelerates data and model reuse in single cell genomics." Genome Biology 22.1 (2021).
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