Quantifying cell-state densities in single-cell phenotypic landscapes using Mellon.

ABSTRACT: Cell-state density characterizes the distribution of cells along phenotypic landscapes and is crucial for unraveling the mechanisms that drive diverse biological processes. Here, we present Mellon, an algorithm for estimation of cell-state densities from high-dimensional representations of single-cell data. We demonstrate Mellon's efficacy by dissecting the density landscape of differentiating systems, revealing a consistent pattern of high-density regions corresponding to major cell types intertwined with low-density, rare transitory states. We present evidence implicating enhancer priming and the activation of master regulators in emergence of these transitory states. Mellon offers the flexibility to perform temporal interpolation of time-series data, providing a detailed view of cell-st

SUBMITTER: Otto DJ 

PROVIDER: S-EPMC12265947 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature