Single-cell RNA sequencing methods can profile the transcriptomes of single cells but cannot preserve spatial information. Conversely, spatial transcriptomics assays can profile spatial regions in tissue sections, but do not have single-cell resolution. Here, we developed a computational method called Ce...
While single-cell RNA-seq (scRNA-seq) can identify cell types and their states at high resolution within tissues, it lacks the capability to pinpoint their spatial distribution or capture the local cell–cell interactions as well as ligands and receptors that mediate these interactions. Therefore,...
In contrast to whole tissue RNA sequencing analysis, single-cell RNA-sequencing (scRNA-seq) and spatial transcriptomics enables the study of transcriptional activity at the single cell or spatial level. ScRNA-seq has paved the way for the discovery of previously unknown cell types and subtypes in...
A research team led by Zhang Hongbo, a professor at the Zhongshan School of Medicine at Sun Yat-sen University, innovatively used single cell transcriptome technology and single cell spatial transcriptome technology, making it possible to explore the cell evolution process. The researchers sampled embr...
Tertiary lymphoid structures are immune cell aggregates linked with cancer outcomes, but their interactions with tumour cell aggregates are unclear. Using nasopharyngeal carcinoma as a model, here we analyse single-cell transcriptomes of 343,829 cells fr
The development of single-cell technologies yields large datasets of information as diverse and multimodal as transcriptomes, immunophenotypes, and spatial position from tissue sections in the so-called ’spatial transcriptomics’. Currently however, user-friendly, powerful, and free algorithmic tools for...
(C) Predicted spatial distributions of RG, IPC/TAC, and neuron subclusters in the PCW4 spatial transcriptome. (D) Sankey diagram mapping the cell fate trajectories from RG subclusters to neurons through IPC/TAC cells. The edge width represents the transcriptional correlation between subclusters. ...
Single-cell sequencingTranscriptomeBioinformatic methodsApplicationsSpatial transcriptomicsMulti-omicsSingle-cell sequencing was developed as a high-throughput tool to elucidate unusual and transient cell states that are barely visible in the bulk. This technology reveals the evolutionary status of cells and ...
Recently, the single-cell transcriptome makes possible the in-depth investigation in transcriptional heterogeneity and regulatory mechanism among cell subsets in the developing kidney, providing novel insights into the pathophysiological mechanism for acquired renal disease progression [3,4,5]. These studies...
Context-aware deconvolution of cell-cell communication with Tensor-cell2cell Nat Commun 14.919 Cyclic microchip assay for measurement of hundreds of functional proteins in single neurons Genome Biol 13.583 De novo reconstruction of cell interaction landscapes from single-cell spatial transcriptome data with...