Inconsistencies in naming, processing, and accessibility of single-cell gene expression data from different sources make data integration a challenging task for biologists.
Geneformer, a deep-learning model by Christina Theodoris, streamlines analysis by predicting gene perturbations impact using aggregated single-cell transcriptomic data, but manual data collection from multiple sources remains time-consuming.
Chan Zuckerberg CELL by GENE Discover (CZ CELLxGENE) offers a new resource with open-source tools for fast and efficient access to curated single-cell data, significantly reducing the time required for data collection and processing.
#single-cell-gene-expression-data #data-integration #biologists #chan-zuckerberg-initiative #data-processing
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