The recent boom in microfluidics and combinatorial indexing strategies, combined with low
sequencing costs, has empowered single-cell sequencing technology. Thousands—or even …

Recent technological advancements have enabled the profiling of a large number of
genome-wide features in individual cells. However, single-cell data present unique …

Generative pretrained models have achieved remarkable success in various domains such
as language and computer vision. Specifically, the combination of large-scale diverse …

To the Editor—Methods for analyzing single-cell data 1, 2, 3, 4 perform a core set of
computational tasks. These tasks include dimensionality reduction, cell clustering, cell-state …

In recent years, single-cell RNA sequencing (scRNA-seq) has emerged as a powerful
technique for investigating cellular heterogeneity and structure. However, analyzing scRNA …

High-grade serous ovarian cancer (HGSOC) is an archetypal cancer of genomic instability,,–
patterned by distinct mutational processes,, tumour heterogeneity,–and intraperitoneal …

The stromal compartment of the tumor microenvironment consists of a heterogeneous set of
tissue-resident and tumor-infiltrating cells, which are profoundly moulded by cancer cells. An …

Biological heterogeneity in diffuse large B cell lymphoma (DLBCL) is partly driven by cell-of-
origin subtypes and associated genomic lesions, but also by diverse cell types and cell …

The advent of single-cell RNA sequencing (scRNA-seq) has provided insight into the tumour
immune microenvironment (TIME). This review focuses on the application of scRNA-seq in …

Single-cell transcriptomics offers unprecedented opportunities to infer the ligand–receptor
(LR) interactions underlying cellular networks. We introduce a new, curated LR database …