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Sfaira accelerates data and model reuse in single cell genomics.
Genome Biol. 22:248 (2021)
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.
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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
Data Zoo ; Model Zoo ; Single-cell Genomics; Atlas
ISSN (print) / ISBN
1474-760X
e-ISSN
1465-6906
Journal
Genome Biology
Quellenangaben
Volume: 22,
Issue: 1,
Article Number: 248
Publisher
BioMed Central
Publishing Place
Campus, 4 Crinan St, London N1 9xw, England
Non-patent literature
Publications
Reviewing status
Peer reviewed
Institute(s)
Institute of Computational Biology (ICB)
Helmholtz AI - HMGU (HAI - HMGU)
Helmholtz AI - HMGU (HAI - HMGU)
Grants
Joachim Herz Stiftung
Helmholtz Zentrum Munchen
Deutsche Forschungsgemeinschaft
Helmholtz Zentrum Munchen
Deutsche Forschungsgemeinschaft