cff-version: 1.2.0
abstract: "<p>Scripts and data for the paper: Consequences and opportunities arising due to sparser single-cell RNA-seq datasets</p><p><br></p><p>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.</p>"
authors:
  - family-names: Bouland
    given-names: Gerard
    orcid: "https://orcid.org/0000-0002-4311-8725"
  - family-names: Reinders
    given-names: Marcel
  - family-names: Mahfouz
    given-names: Ahmed
    orcid: "https://orcid.org/0000-0001-8601-2149"
title: "Scripts and data for the paper: Consequences and opportunities arising due to sparser single-cell RNA-seq datasets"
keywords:
version: 1
identifiers:
  - type: doi
    value: 10.4121/424eea7a-cce9-4dbb-b6ef-e5b47e132410.v1
license: MIT
date-released: 2024-10-15