Differential analysis of binarized single-cell RNA sequencing data captures biological variation

NAR Genomics and Bioinformatics, vol. 3, pp. lqab118

Abstract

Single-cell RNA sequencing data is characterized by a large number of zero counts, yet there is growing evidence that these zeros reflect biological variation rather than technical artifacts. We propose to use binarized expression profiles to identify the effects of biological variation in single-cell RNA sequencing data. Using 16 publicly available and simulated datasets, we show that a binarized representation of single-cell expression data accurately represents biological variation and reveals the relative abundance of transcripts more robustly than counts.

Authors 3

1. Gerard A. Bouland Aachen Department of Human Genetics

   Leiden University Medical Center · Delft University of Technology

   Affiliation as printed

   Delft Bioinformatics Lab, Delft University of Technology, Delft 2628 XE, The Netherlands

   Department of Human Genetics, Leiden University Medical Center, Leiden 2333ZC, The Netherlands

2. Ahmed Essam Mahfouz corresponding Aachen Department of Human Genetics Leiden Computational Biology Center

   Leiden University Medical Center · Delft University of Technology

   Affiliation as printed

   Delft Bioinformatics Lab, Delft University of Technology, Delft 2628 XE, The Netherlands

   Department of Human Genetics, Leiden University Medical Center, Leiden 2333ZC, The Netherlands

   Leiden Computational Biology Center, Leiden University Medical Center, Leiden 2333ZC, The Netherlands

3. Marcel J. T. Reinders corresponding Aachen Department of Human Genetics Leiden Computational Biology Center

   Leiden University Medical Center · Delft University of Technology

   Affiliation as printed

   Delft Bioinformatics Lab, Delft University of Technology, Delft 2628 XE, The Netherlands

   Department of Human Genetics, Leiden University Medical Center, Leiden 2333ZC, The Netherlands

   Leiden Computational Biology Center, Leiden University Medical Center, Leiden 2333ZC, The Netherlands