Computational flow cytometric analysis to detect epidermal subpopulations in human skin.

ABSTRACT:

Background

The detection and dissection of epidermal subgroups could lead to an improved understanding of skin homeostasis and wound healing. Flow cytometric analysis provides an effective method to detect the surface markers of epidermal cells while producing high-dimensional data files.

Methods

A 9-color flow cytometric panel was optimized to reveal the heterogeneous subgroups in the epidermis of human skin. The subsets of epidermal cells were characterized using automated methods based on dimensional reduction approaches (viSNE) and clustering with Spanning-tree Progression Analysis of Density-normalized Events (SPADE).

Results

The manual analysis revealed differences in epidermal distribution between body sites based on a series biaxial gating starting with the ex

SUBMITTER: Zhang L 

PROVIDER: S-EPMC7891025 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature