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

Highlights•New methods enable insights into mutation burden in normal tissues.•Mutation
burden rises with age, varying across cell types and species.•Insights into regulating …

Single‐cell analyses can be confounded by assigning unrelated groups of cells to common
developmental trajectories. For instance, cancer cells and admixed normal epithelial cells …

Temporal ordering of cellular events offers fundamental insights into biological phenomena.
Although this is traditionally achieved through continuous direct observations 1, 2, an …

Investigating mutations, including single nucleotide variations (SNVs), gene fusions,
alternative splicing and copy number variations (CNVs), is fundamental to cancer study …

The rapid evolution of mass spectrometry-based single-cell proteomics now enables the
cataloging of several thousand proteins from single cells. We investigated whether we could …

Identifying expressed somatic mutations from single-cell RNA sequencing data de novo is
challenging but highly valuable. We propose RESA–Recurrently Expressed SNV Analysis, a …

Motivation Single-cell RNA sequencing (scRNA-seq) data are widely used to study cancer
cell states and their heterogeneity. However, the tumour microenvironment is usually a …

Background Myelodysplastic syndrome (MDS) is a complicated hematopoietic malignancy
characterized by bone marrow (BM) dysplasia with symptoms like anemia, neutropenia, or …

Developmental dynamics encompass both the specification of cell types and their spatial
organisation into multicellular niches. Here we harness the power of single-cell and spatial …