Recent advances in single-cell technologies have enabled high-throughput molecular
profiling of cells across modalities and locations. Single-cell transcriptomics data can now …

Single-cell transcriptomics (scRNA-seq) has become essential for biomedical research over
the past decade, particularly in developmental biology, cancer, immunology, and …

Spatial clustering, which shares an analogy with single-cell clustering, has expanded the
scope of tissue physiology studies from cell-centroid to structure-centroid with spatially …

The function of a cell is defined by its intrinsic characteristics and its niche: the tissue
microenvironment in which it dwells. Here we combine single-cell and spatial …

Single-cell and spatial technologies that profile gene expression across a whole tissue are
revolutionizing the resolution of molecular states in clinical samples. Current commercially …

Spatial transcriptomics technologies generate gene expression profiles with spatial context,
requiring spatially informed analysis tools for three key tasks, spatial clustering, multisample …

Single-cell omics technologies have enabled the creation of comprehensive cell atlases
across tissues and species and delivered key insights into the biological mechanisms …

Spatial transcriptomics technologies are used to profile transcriptomes while preserving
spatial information, which enables high-resolution characterization of transcriptional patterns …

Single-cell transcriptomics has broadened our understanding of cellular diversity and gene
expression dynamics in healthy and diseased tissues. Recently, spatial transcriptomics has …

High-grade serous ovarian carcinoma (HGSOC) is genetically unstable and characterised
by the presence of subclones with distinct genotypes. Intratumoural heterogeneity is linked …