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• W4366606312 abstract "Abstract With the number of cells measured in single-cell RNA sequencing (scRNA-seq) datasets increasing exponentially and concurrent increased sparsity due to more zero counts being measured for many genes, we demonstrate here that downstream analyses on binary-based gene expression give similar results as count-based analyses. Moreover, a binary representation scales up to ~ 50-fold more cells that can be analyzed using the same computational resources. We also highlight the possibilities provided by binarized scRNA-seq data. Development of specialized tools for bit-aware implementations of downstream analytical tasks will enable a more fine-grained resolution of biological heterogeneity." @default.
• W4366606312 created "2023-04-23" @default.
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• W4366606312 date "2023-04-21" @default.
• W4366606312 modified "2023-09-26" @default.
• W4366606312 title "Consequences and opportunities arising due to sparser single-cell RNA-seq datasets" @default.
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• W4366606312 doi "https://doi.org/10.1186/s13059-023-02933-w" @default.
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