TY - DATA
T1 - Scripts and data for the paper: Differential analysis of binarized single-cell RNA sequencing data captures biological variation
PY - 2024/10/15
AU - Gerard Bouland
AU - Marcel Reinders
AU - Ahmed Mahfouz
UR - 
DO - 10.4121/618e2cdb-d961-45c0-ab72-09bd68827580.v1
KW - scRNAseq
KW - gene expression
KW - binary
KW - Single cell RNA sequencing
KW - binarized expression
N2 - <p>Scripts and data for the paper: Differential analysis of binarized single-cell RNA sequencing data captures biological variation</p><p><br></p><p>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.</p><p><br></p>
ER -