BCseq: accurate single cell RNA-seq quantification with bias correction
With rapid technical advances, single cell RNA-seq (scRNA-seq) has been used to detect
cell subtypes exhibiting distinct gene expression profiles and to trace cell transitions in …
cell subtypes exhibiting distinct gene expression profiles and to trace cell transitions in …
Identifying cell types to interpret scRNA-seq data: how, why and more possibilities
Single-cell RNA sequencing (scRNA-seq) has generated numerous data and renewed our
understanding of biological phenomena at the cellular scale. Identification of cell types has …
understanding of biological phenomena at the cellular scale. Identification of cell types has …
scID uses discriminant analysis to identify transcriptionally equivalent cell types across single-cell RNA-seq data with batch effect
The power of single-cell RNA sequencing (scRNA-seq) stems from its ability to uncover cell
type-dependent phenotypes, which rests on the accuracy of cell type identification. However …
type-dependent phenotypes, which rests on the accuracy of cell type identification. However …
scNPF: an integrative framework assisted by network propagation and network fusion for preprocessing of single-cell RNA-seq data
Background Single-cell RNA-sequencing (scRNA-seq) is fast becoming a powerful tool for
profiling genome-scale transcriptomes of individual cells and capturing transcriptome-wide …
profiling genome-scale transcriptomes of individual cells and capturing transcriptome-wide …
scID: identification of transcriptionally equivalent cell populations across single cell RNA-seq data using discriminant analysis
The power of single cell RNA sequencing (scRNA-seq) stems from its ability to uncover cell
type-dependent phenotypes, which rests on the accuracy of cell type identification. However …
type-dependent phenotypes, which rests on the accuracy of cell type identification. However …
[HTML][HTML] Identifying cell populations with scRNASeq
TS Andrews, M Hemberg - Molecular aspects of medicine, 2018 - Elsevier
Single-cell RNASeq (scRNASeq) has emerged as a powerful method for quantifying the
transcriptome of individual cells. However, the data from scRNASeq experiments is often …
transcriptome of individual cells. However, the data from scRNASeq experiments is often …
SC1: a tool for interactive web-based single-cell RNA-Seq data analysis
M Moussa, II Măndoiu - Journal of Computational Biology, 2021 - liebertpub.com
Single-cell RNA-Seq (scRNA-Seq) is critical for studying cellular function and phenotypic
heterogeneity as well as the development of tissues and tumors. In this study, we present …
heterogeneity as well as the development of tissues and tumors. In this study, we present …
Comparative analysis of NovaSeq 6000 and MGISEQ 2000 single‐cell RNA sequencing data
W Chen, M Wahiduzzaman, Q Li, Y Li… - Quantitative …, 2022 - Wiley Online Library
Background Single‐cell RNA sequencing (scRNA‐seq) technology is now becoming a
widely applied method of transcriptome exploration that helps to reveal cell‐type …
widely applied method of transcriptome exploration that helps to reveal cell‐type …
[HTML][HTML] An accessible, interactive GenePattern Notebook for analysis and exploration of single-cell transcriptomic data
Single-cell RNA sequencing (scRNA-seq) has emerged as a popular method to profile gene
expression at the resolution of individual cells. While there have been methods and software …
expression at the resolution of individual cells. While there have been methods and software …
ClusterMap: compare multiple single cell RNA-Seq datasets across different experimental conditions
Abstract Motivation Single cell RNA-Seq (scRNA-Seq) facilitates the characterization of cell
type heterogeneity and developmental processes. Further study of single cell profiles across …
type heterogeneity and developmental processes. Further study of single cell profiles across …