A comprehensive survey of statistical approaches for differential expression analysis in single-cell RNA sequencing studies

S Das, A Rai, ML Merchant, MC Cave, SN Rai - Genes, 2021 - mdpi.com
Single-cell RNA-sequencing (scRNA-seq) is a recent high-throughput sequencing
technique for studying gene expressions at the cell level. Differential Expression (DE) …

Differential expression analyses for single-cell RNA-Seq: old questions on new data

Z Miao, X Zhang - Quantitative Biology, 2016 - Springer
Background Single-cell RNA sequencing (scRNA-seq) is an emerging technology that
enables high resolution detection of heterogeneities between cells. One important …

[HTML][HTML] SwarnSeq: An improved statistical approach for differential expression analysis of single-cell RNA-seq data

S Das, SN Rai - Genomics, 2021 - Elsevier
Single-cell RNA sequencing (scRNA-seq) is a powerful technology that is capable of
generating gene expression data at the resolution of individual cell. The scRNA-seq data is …

Reproducibility of methods to detect differentially expressed genes from single-cell RNA sequencing

T Mou, W Deng, F Gu, Y Pawitan, TN Vu - Frontiers in genetics, 2020 - frontiersin.org
Detection of differentially expressed genes is a common task in single-cell RNA-seq (scRNA-
seq) studies. Various methods based on both bulk-cell and single-cell approaches are in …

Comparative analysis of differential gene expression analysis tools for single-cell RNA sequencing data

T Wang, B Li, CE Nelson, S Nabavi - BMC bioinformatics, 2019 - Springer
Background The analysis of single-cell RNA sequencing (scRNAseq) data plays an
important role in understanding the intrinsic and extrinsic cellular processes in biological …

A systematic evaluation of single cell RNA-seq analysis pipelines

B Vieth, S Parekh, C Ziegenhain, W Enard… - Nature …, 2019 - nature.com
The recent rapid spread of single cell RNA sequencing (scRNA-seq) methods has created a
large variety of experimental and computational pipelines for which best practices have not …

Differential expression analysis of single-cell rna-seq data: current statistical approaches and outstanding challenges

S Das, A Rai, SN Rai - Entropy, 2022 - mdpi.com
With the advent of single-cell RNA-sequencing (scRNA-seq), it is possible to measure the
expression dynamics of genes at the single-cell level. Through scRNA-seq, a huge amount …

scDEA: differential expression analysis in single-cell RNA-sequencing data via ensemble learning

HS Li, L Ou-Yang, Y Zhu, H Yan… - Briefings in …, 2022 - academic.oup.com
The identification of differentially expressed genes between different cell groups is a crucial
step in analyzing single-cell RNA-sequencing (scRNA-seq) data. Even though various …

Single-cell RNA-seq technologies and related computational data analysis

G Chen, B Ning, T Shi - Frontiers in genetics, 2019 - frontiersin.org
Single-cell RNA sequencing (scRNA-seq) technologies allow the dissection of gene
expression at single-cell resolution, which greatly revolutionizes transcriptomic studies. A …

A statistical simulator scDesign for rational scRNA-seq experimental design

WV Li, JJ Li - Bioinformatics, 2019 - academic.oup.com
Motivation Single-cell RNA sequencing (scRNA-seq) has revolutionized biological sciences
by revealing genome-wide gene expression levels within individual cells. However, a critical …