Clustering single cells: a review of approaches on high-and low-depth single-cell RNA-seq data
V Menon - Briefings in functional genomics, 2018 - academic.oup.com
Advances in single-cell RNA-sequencing technology have resulted in a wealth of studies
aiming to identify transcriptomic cell types in various biological systems. There are multiple …
aiming to identify transcriptomic cell types in various biological systems. There are multiple …
Impact of data preprocessing on cell-type clustering based on single-cell RNA-seq data
C Wang, X Gao, J Liu - BMC bioinformatics, 2020 - Springer
Background Advances in single-cell RNA-seq technology have led to great opportunities for
the quantitative characterization of cell types, and many clustering algorithms have been …
the quantitative characterization of cell types, and many clustering algorithms have been …
Accounting for cell type hierarchy in evaluating single cell RNA-seq clustering
Cell clustering is one of the most common routines in single cell RNA-seq data analyses, for
which a number of specialized methods are available. The evaluation of these methods …
which a number of specialized methods are available. The evaluation of these methods …
Review of single-cell RNA-seq data clustering for cell-type identification and characterization
In recent years, the advances in single-cell RNA-seq techniques have enabled us to perform
large-scale transcriptomic profiling at single-cell resolution in a high-throughput manner …
large-scale transcriptomic profiling at single-cell resolution in a high-throughput manner …
Identification of cell types from single cell data using stable clustering
Single-cell RNA-seq (scRNASeq) has become a powerful technique for measuring the
transcriptome of individual cells. Unlike the bulk measurements that average the gene …
transcriptome of individual cells. Unlike the bulk measurements that average the gene …
Autoencoder-based cluster ensembles for single-cell RNA-seq data analysis
Background Single-cell RNA-sequencing (scRNA-seq) is a transformative technology,
allowing global transcriptomes of individual cells to be profiled with high accuracy. An …
allowing global transcriptomes of individual cells to be profiled with high accuracy. An …
FEATS: feature selection-based clustering of single-cell RNA-seq data
Motivation Advances in next-generation sequencing have made it possible to carry out
transcriptomic studies at single-cell resolution and generate vast amounts of single-cell RNA …
transcriptomic studies at single-cell resolution and generate vast amounts of single-cell RNA …
SAIC: an iterative clustering approach for analysis of single cell RNA-seq data
Background Research interests toward single cell analysis have greatly increased in basic,
translational and clinical research areas recently, as advances in whole-transcriptome …
translational and clinical research areas recently, as advances in whole-transcriptome …
PanoView: An iterative clustering method for single-cell RNA sequencing data
Single-cell RNA-sequencing (scRNA-seq) provides new opportunities to gain a mechanistic
understanding of many biological processes. Current approaches for single cell clustering …
understanding of many biological processes. Current approaches for single cell clustering …
An interpretable framework for clustering single-cell RNA-Seq datasets
Background With the recent proliferation of single-cell RNA-Seq experiments, several
methods have been developed for unsupervised analysis of the resulting datasets. These …
methods have been developed for unsupervised analysis of the resulting datasets. These …