Best practices for single-cell analysis across modalities
Recent advances in single-cell technologies have enabled high-throughput molecular
profiling of cells across modalities and locations. Single-cell transcriptomics data can now …
profiling of cells across modalities and locations. Single-cell transcriptomics data can now …
A reference cell tree will serve science better than a reference cell atlas
Single-cell biology is facing a crisis of sorts. Vast numbers of single-cell molecular profiles
are being generated, clustered and annotated. However, this is overwhelmingly ad hoc, and …
are being generated, clustered and annotated. However, this is overwhelmingly ad hoc, and …
scBERT as a large-scale pretrained deep language model for cell type annotation of single-cell RNA-seq data
Annotating cell types on the basis of single-cell RNA-seq data is a prerequisite for research
on disease progress and tumour microenvironments. Here we show that existing annotation …
on disease progress and tumour microenvironments. Here we show that existing annotation …
Advances in spatial transcriptomic data analysis
Spatial transcriptomics is a rapidly growing field that promises to comprehensively
characterize tissue organization and architecture at the single-cell or subcellular resolution …
characterize tissue organization and architecture at the single-cell or subcellular resolution …
Consensus prediction of cell type labels in single-cell data with popV
Cell-type classification is a crucial step in single-cell sequencing analysis. Various methods
have been proposed for transferring a cell-type label from an annotated reference atlas to …
have been proposed for transferring a cell-type label from an annotated reference atlas to …
Single-cell transcriptomics for the assessment of cardiac disease
AMA Miranda, V Janbandhu, H Maatz… - Nature Reviews …, 2023 - nature.com
Cardiovascular disease is the leading cause of death globally. An advanced understanding
of cardiovascular disease mechanisms is required to improve therapeutic strategies and …
of cardiovascular disease mechanisms is required to improve therapeutic strategies and …
Spatial omics: Navigating to the golden era of cancer research
The idea that tumour microenvironment (TME) is organised in a spatial manner will not
surprise many cancer biologists; however, systematically capturing spatial architecture of …
surprise many cancer biologists; however, systematically capturing spatial architecture of …
Biologically informed deep learning to query gene programs in single-cell atlases
The increasing availability of large-scale single-cell atlases has enabled the detailed
description of cell states. In parallel, advances in deep learning allow rapid analysis of newly …
description of cell states. In parallel, advances in deep learning allow rapid analysis of newly …
Data analysis guidelines for single-cell RNA-seq in biomedical studies and clinical applications
M Su, T Pan, QZ Chen, WW Zhou, Y Gong, G Xu… - Military Medical …, 2022 - Springer
The application of single-cell RNA sequencing (scRNA-seq) in biomedical research has
advanced our understanding of the pathogenesis of disease and provided valuable insights …
advanced our understanding of the pathogenesis of disease and provided valuable insights …
scDeepSort: a pre-trained cell-type annotation method for single-cell transcriptomics using deep learning with a weighted graph neural network
Advances in single-cell RNA sequencing (scRNA-seq) have furthered the simultaneous
classification of thousands of cells in a single assay based on transcriptome profiling. In …
classification of thousands of cells in a single assay based on transcriptome profiling. In …