Alignment of single-cell trajectories by tuMap enables high-resolution quantitative comparison of cancer samples.

ABSTRACT: Single-cell technologies allow characterization of cancer samples as continuous developmental trajectories. Yet, the obtained temporal resolution cannot be leveraged for a comparative analysis due to the large phenotypic heterogeneity existing between patients. Here, we present the tuMap algorithm that exploits high-dimensional single-cell data of cancer samples exhibiting an underlying developmental structure to align them with the healthy development, yielding the tuMap pseudotime axis that allows their systematic, meaningful comparison. We applied tuMap on single-cell mass cytometry data of acute lymphoblastic and myeloid leukemia to reveal associations between the tuMap pseudotime axis and clinics that outperform cellular assignment into developmental populations. Application of the tu

SUBMITTER: Alpert A 

PROVIDER: S-EPMC8776581 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature