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Sfaira accelerates data and model reuse in single cell genomics
- 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