Single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) have opened up new avenues that will expand our knowledge on cellular heterogeneity and ...

R package that automatically classifies the cells in the scRNA data by segregating non-malignant cells of tumor microenviroment from the malignant cells. It also infers the copy number profile of ...

The authors developed a novel tool, SCellBOW, to perform cell clustering and infer survival risks on individual cancer cell clusters from the single cell RNA seq dataset. The key ideas/techniques used ...

This review integrates recent advancements in single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics to elucidate glioblastoma’s cellular heterogeneity and metabolic reprogramming. Diverse ...

Bruker Spatial Biology, Seattle, WA.

Single-cell RNA-sequencing (scRNA-seq) coupled with robust computational analysis facilitates the characterization ... We could trace this back in a large-scale spatial omics atlas of 141 ...

Their work generates extensive multi-modal datasets using contemporary technologies including single-cell RNA sequencing (scRNA-seq), spatial transcriptomics, and multiplex immunohistochemistry.