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Sfaira accelerates data and model reuse in single cell genomics

Authors :
David S. Fischer
Leander Dony
Martin König
Abdul Moeed
Luke Zappia
Lukas Heumos
Sophie Tritschler
Olle Holmberg
Hananeh Aliee
Fabian J. Theis
Source :
Genome Biology, Vol 22, Iss 1, Pp 1-21 (2021)
Publication Year :
2021
Publisher :
BMC, 2021.

Abstract

Abstract 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.

Details

Language :
English
ISSN :
1474760X
Volume :
22
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Genome Biology
Publication Type :
Academic Journal
Accession number :
edsdoj.42d3581d43904bdf861e73681f736824
Document Type :
article
Full Text :
https://doi.org/10.1186/s13059-021-02452-6