Consequences and opportunities arising due to sparser single-cell RNA-seq datasets

Bouland, G.A.; Mahfouz, A.; Reinders, M.J.T. (2023)

Article / Letter to editor

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 similar 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.

• All authors: Bouland, G.A.; Mahfouz, A.; Reinders, M.J.T.
• Date: 2023-04-21
• Journal: Genome Biology
• Volume: 24
• Issue: 1
• DOI: doi:10.1186/s13059-023-02933-w
• Link: https://genomebiology.biomedcentral.com/articles/10.1186/s13059-023-02933-w