Copy number alteration heterogeneity exists in many shapes and forms in breast cancer genomes and single-cell genomics is a powerful tool to further our understanding of its nature and significance.

Single cell expression data can be used to determine how regulatory transcription factors and target genes are connected, and is especially useful when studying transcription factors controlling heterogeneous cell states.

Single cell analysis reveals how period differences between cells and cell-to-cell coupling generates the spatial structure of the plant circadian clock.

Single-cell and bulk expression analyses reveal that HCMV latent infection drives cells towards a weaker immune-responsive state, which is important for its expression and reactivation.

A new method that measures multiple aspects of chromatin organization in single cells has a possible application to study regulatory processes in heterogeneous samples.

An iterative self-assembling algorithm identifies the intrinsic structures in single-cell transcriptomic data and helps to discover new cell populations that are undetectable by existing methods.

Single-cell RNA-seq analysis reveals an increased complexity of mosquito hemocytes, enabling the functional and molecular characterization of immune cell sub-populations in Anopheles gambiae.

Infrared laser-mediated gene induction microscopy enables precise single-cell labeling in various tissues of zebrafish, and in vivo visualized single-cell lineage tracing reveals the lineage heterogeneity in hematopoietic endothelial cells.

Combination of experimental mouse models with single-cell RNA-sequencing creates a detailed map of medullary thymic epithelial cell development and identifies a transit-amplifying population as the immediate precursor to Aire-expressing mTECs.

Single-cell RNA analysis of brain endothelium identifies the angiogenic venous capillary subset and respective resident endothelial progenitors at the origin of CCM lesions, while arterial endothelial cells are unaffected.