Accurate estimation of pathway activity in single cells for clustering and differential analysis.

Inferring which and how biological pathways and gene sets change is a key question in many studies that utilize single-cell RNA sequencing. Typically, these questions are addressed by quantifying the enrichment of known gene sets in lists of genes derived from global analysis. Here we offer SiPSiC, a new method to infer pathway activity in every single cell.

Single-cell RNA sequencing identifies a paracrine interaction that may drive oncogenic notch signaling in human adenoid cystic carcinoma.

Salivary adenoid cystic carcinoma (ACC) is a rare, biologically unique biphasic tumor that consists of malignant myoepithelial and luminal cells. MYB and Notch signaling have been implicated in ACC pathophysiology, but in vivo descriptions of these two programs in human tumors and investigation into their active coordination remain incomplete. We utilize single-cell RNA sequencing to profile human head and neck ACC, including a comparison of primary ACC with a matched local recurrence.