Print Email Facebook Twitter Consequences and opportunities arising due to sparser single-cell RNA-seq datasets Title Consequences and opportunities arising due to sparser single-cell RNA-seq datasets Author Bouland, G.A. (TU Delft Pattern Recognition and Bioinformatics; Leiden University Medical Center) Mahfouz, A.M.E.T.A. (TU Delft Pattern Recognition and Bioinformatics; Leiden University Medical Center) Reinders, M.J.T. (TU Delft Pattern Recognition and Bioinformatics; Leiden University Medical Center) Date 2023 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. Subject OA-Fund TU Delft To reference this document use: http://resolver.tudelft.nl/uuid:c3490c95-95b0-43af-bf2c-3a1b97334d86 DOI https://doi.org/10.1186/s13059-023-02933-w ISSN 1474-760X Source Genome Biology (Online), 24 (1) Part of collection Institutional Repository Document type journal article Rights © 2023 G.A. Bouland, A.M.E.T.A. Mahfouz, M.J.T. Reinders Files PDF s13059_023_02933_w.pdf 6.11 MB Close viewer /islandora/object/uuid:c3490c95-95b0-43af-bf2c-3a1b97334d86/datastream/OBJ/view