Researchers view vast zeros in single-cell RNA-seq data differently: some regard zeros as
biological signals representing no or low gene expression, while others regard zeros as …

Background Single-cell RNA sequencing is a powerful tool for characterizing cellular
heterogeneity in gene expression. However, high variability and a large number of zero …

Dropout events in single-cell RNA sequencing (scRNA-seq) cause many transcripts to go
undetected and induce an excess of zero read counts, leading to power issues in differential …

Single cell RNA-sequencing (scRNA-seq) methods have revolutionized the study of gene
expression but are plagued by dropout events, a phenomenon where genes actually …

The excessive amount of zeros in single-cell RNA-seq (scRNA-seq) data includes 'real'zeros
due to the on-off nature of gene transcription in single cells and 'dropout'zeros due to …

Single-cell RNA-sequencing (scRNA-seq) is a powerful high-throughput technique that
enables researchers to measure genome-wide transcription levels at the resolution of single …

Genomic studies feature multivariate count data from high-throughput DNA sequencing
experiments, which often contain many zero values. These zeros can cause artifacts for …

Background The single cell RNA sequencing (scRNA-seq) technique begin a new era by
allowing the observation of gene expression at the single cell level. However, there is also a …

A key challenge in analyzing single cell RNA-sequencing data is the large number of false
zeros, where genes actually expressed in a given cell are incorrectly measured as …

Background Heterogeneity in single-cell RNA-seq (scRNA-seq) data is driven by multiple
sources, including biological variation in cellular state as well as technical variation …