Profiling cell identity and tissue architecture with single-cell and spatial transcriptomics
Single-cell transcriptomics has broadened our understanding of cellular diversity and gene
expression dynamics in healthy and diseased tissues. Recently, spatial transcriptomics has …
expression dynamics in healthy and diseased tissues. Recently, spatial transcriptomics has …
Application of deep learning on single-cell RNA sequencing data analysis: a review
Single-cell RNA sequencing (scRNA-seq) has become a routinely used technique to
quantify the gene expression profile of thousands of single cells simultaneously. Analysis of …
quantify the gene expression profile of thousands of single cells simultaneously. Analysis of …
SpaGCN: Integrating gene expression, spatial location and histology to identify spatial domains and spatially variable genes by graph convolutional network
Recent advances in spatially resolved transcriptomics (SRT) technologies have enabled
comprehensive characterization of gene expression patterns in the context of tissue …
comprehensive characterization of gene expression patterns in the context of tissue …
Human Alzheimer's disease reactive astrocytes exhibit a loss of homeostastic gene expression
Astrocytes are one of the brain's major cell types and are responsible for maintaining
neuronal homeostasis via regulating the extracellular environment, providing metabolic …
neuronal homeostasis via regulating the extracellular environment, providing metabolic …
Graph-based autoencoder integrates spatial transcriptomics with chromatin images and identifies joint biomarkers for Alzheimer's disease
Tissue development and disease lead to changes in cellular organization, nuclear
morphology, and gene expression, which can be jointly measured by spatial transcriptomic …
morphology, and gene expression, which can be jointly measured by spatial transcriptomic …
GSEApy: a comprehensive package for performing gene set enrichment analysis in Python
Z Fang, X Liu, G Peltz - Bioinformatics, 2023 - academic.oup.com
Motivation Gene set enrichment analysis (GSEA) is a commonly used algorithm for
characterizing gene expression changes. However, the currently available tools used to …
characterizing gene expression changes. However, the currently available tools used to …
Gastric Microbiome Alterations Are Associated with Decreased CD8+ Tissue-Resident Memory T Cells in the Tumor Microenvironment of Gastric Cancer
R Peng, S Liu, W You, Y Huang, C Hu, Y Gao… - Cancer immunology …, 2022 - AACR
The host microbiota is closely associated with tumor initiation and progression in multiple
solid tumors including gastric cancer. The aim of this study was to investigate in patients with …
solid tumors including gastric cancer. The aim of this study was to investigate in patients with …
Batch alignment of single-cell transcriptomics data using deep metric learning
X Yu, X Xu, J Zhang, X Li - Nature communications, 2023 - nature.com
Abstract scRNA-seq has uncovered previously unappreciated levels of heterogeneity. With
the increasing scale of scRNA-seq studies, the major challenge is correcting batch effect …
the increasing scale of scRNA-seq studies, the major challenge is correcting batch effect …
High-dimensional single-cell multimodal landscape of human carotid atherosclerosis
BACKGROUND: Atherosclerotic plaques are complex tissues composed of a
heterogeneous mixture of cells. However, our understanding of the comprehensive …
heterogeneous mixture of cells. However, our understanding of the comprehensive …
scLEGA: an attention-based deep clustering method with a tendency for low expression of genes on single-cell RNA-seq data
Z Liu, Y Liang, G Wang, T Zhang - Briefings in Bioinformatics, 2024 - academic.oup.com
Single-cell RNA sequencing (scRNA-seq) enables the exploration of biological
heterogeneity among different cell types within tissues at a resolution. Inferring cell types …
heterogeneity among different cell types within tissues at a resolution. Inferring cell types …