Consequences and Opportunities Arising Due to Sparser Single-cell RNA-seq Datasets

Overview

Journal Genome Biol

Specialties Biology
Genetics

Date 2023 Apr 21

PMID 37085823

Authors

Gerard A Bouland

Ahmed Mahfouz

Marcel J T Reinders

Affiliations

Soon will be listed here.

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.

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