Single-cell and spatial transcriptomics: deciphering brain complexity in health and disease
In the past decade, single-cell technologies have proliferated and improved from their
technically challenging beginnings to become common laboratory methods capable of …
technically challenging beginnings to become common laboratory methods capable of …
Eleven grand challenges in single-cell data science
The recent boom in microfluidics and combinatorial indexing strategies, combined with low
sequencing costs, has empowered single-cell sequencing technology. Thousands—or even …
sequencing costs, has empowered single-cell sequencing technology. Thousands—or even …
Benchmarking spatial and single-cell transcriptomics integration methods for transcript distribution prediction and cell type deconvolution
Spatial transcriptomics approaches have substantially advanced our capacity to detect the
spatial distribution of RNA transcripts in tissues, yet it remains challenging to characterize …
spatial distribution of RNA transcripts in tissues, yet it remains challenging to characterize …
[HTML][HTML] Transcriptional programs of neoantigen-specific TIL in anti-PD-1-treated lung cancers
Abstract PD-1 blockade unleashes CD8 T cells, including those specific for mutation-
associated neoantigens (MANA), but factors in the tumour microenvironment can inhibit …
associated neoantigens (MANA), but factors in the tumour microenvironment can inhibit …
[HTML][HTML] Metabolic modeling of single Th17 cells reveals regulators of autoimmunity
Metabolism is a major regulator of immune cell function, but it remains difficult to study the
metabolic status of individual cells. Here, we present Compass, an algorithm to characterize …
metabolic status of individual cells. Here, we present Compass, an algorithm to characterize …
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 …
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 …
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 …
Current best practices in single‐cell RNA‐seq analysis: a tutorial
MD Luecken, FJ Theis - Molecular systems biology, 2019 - embopress.org
Single‐cell RNA‐seq has enabled gene expression to be studied at an unprecedented
resolution. The promise of this technology is attracting a growing user base for single‐cell …
resolution. The promise of this technology is attracting a growing user base for single‐cell …
scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses
Single-cell RNA-sequencing (scRNA-Seq) is widely used to reveal the heterogeneity and
dynamics of tissues, organisms, and complex diseases, but its analyses still suffer from …
dynamics of tissues, organisms, and complex diseases, but its analyses still suffer from …