Statistics or biology: the zero-inflation controversy about scRNA-seq data
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 …
biological signals representing no or low gene expression, while others regard zeros as …
Bayesian model selection reveals biological origins of zero inflation in single-cell transcriptomics
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 …
heterogeneity in gene expression. However, high variability and a large number of zero …
Observation weights unlock bulk RNA-seq tools for zero inflation and single-cell applications
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 …
undetected and induce an excess of zero read counts, leading to power issues in differential …
Zero-preserving imputation of scRNA-seq data using low-rank approximation
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 …
expression but are plagued by dropout events, a phenomenon where genes actually …
DEsingle for detecting three types of differential expression in single-cell RNA-seq data
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 …
due to the on-off nature of gene transcription in single cells and 'dropout'zeros due to …
A general and flexible method for signal extraction from single-cell RNA-seq data
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 …
enables researchers to measure genome-wide transcription levels at the resolution of single …
[HTML][HTML] Naught all zeros in sequence count data are the same
JD Silverman, K Roche, S Mukherjee… - Computational and …, 2020 - Elsevier
Genomic studies feature multivariate count data from high-throughput DNA sequencing
experiments, which often contain many zero values. These zeros can cause artifacts for …
experiments, which often contain many zero values. These zeros can cause artifacts for …
DrImpute: imputing dropout events in single cell RNA sequencing data
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 …
allowing the observation of gene expression at the single cell level. However, there is also a …
Zero-preserving imputation of single-cell RNA-seq data
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 …
zeros, where genes actually expressed in a given cell are incorrectly measured as …
Comparison and evaluation of statistical error models for scRNA-seq
S Choudhary, R Satija - Genome biology, 2022 - Springer
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 …
sources, including biological variation in cellular state as well as technical variation …