Single-cell proteomics enabled by next-generation sequencing or mass spectrometry
In the last decade, single-cell RNA sequencing routinely performed on large numbers of
single cells has greatly advanced our understanding of the underlying heterogeneity of …
single cells has greatly advanced our understanding of the underlying heterogeneity of …
Tutorial: guidelines for the computational analysis of single-cell RNA sequencing data
Single-cell RNA sequencing (scRNA-seq) is a popular and powerful technology that allows
you to profile the whole transcriptome of a large number of individual cells. However, the …
you to profile the whole transcriptome of a large number of individual cells. However, the …
Integrated analysis of multimodal single-cell data
Y Hao, S Hao, E Andersen-Nissen, WM Mauck… - Cell, 2021 - cell.com
The simultaneous measurement of multiple modalities represents an exciting frontier for
single-cell genomics and necessitates computational methods that can define cellular states …
single-cell genomics and necessitates computational methods that can define cellular states …
Comparison and evaluation of statistical error models for scRNA-seq
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 …
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 …
expression at single-cell resolution, which greatly revolutionizes transcriptomic studies. A …
Transcriptional signature in microglia associated with Aβ plaque phagocytosis
The role of microglia cells in Alzheimer's disease (AD) is well recognized, however their
molecular and functional diversity remain unclear. Here, we isolated amyloid plaque …
molecular and functional diversity remain unclear. Here, we isolated amyloid plaque …
Challenges in unsupervised clustering of single-cell RNA-seq data
Single-cell RNA sequencing (scRNA-seq) allows researchers to collect large catalogues
detailing the transcriptomes of individual cells. Unsupervised clustering is of central …
detailing the transcriptomes of individual cells. Unsupervised clustering is of central …
The art of using t-SNE for single-cell transcriptomics
Single-cell transcriptomics yields ever growing data sets containing RNA expression levels
for thousands of genes from up to millions of cells. Common data analysis pipelines include …
for thousands of genes from up to millions of cells. Common data analysis pipelines include …
Orchestrating single-cell analysis with Bioconductor
Recent technological advancements have enabled the profiling of a large number of
genome-wide features in individual cells. However, single-cell data present unique …
genome-wide features in individual cells. However, single-cell data present unique …
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 …