Efficient Integration of Human Skin Single-Cell RNA Sequencing Data

This document presents a comprehensive effort to create an integrated human skin cell atlas, aiming to establish a consensus nomenclature for normal human skin. The study reanalyzed 24 single-cell RNA sequencing datasets, harmonizing metadata and cell annotations, and made the data accessible through "Skin Explorer," an interactive tool. A molecular and spatial atlas of skin fibroblasts was developed, revealing shared disease-related subtypes across tissues. The research also explored the role of miR-149 in skin inflammation using mouse and human models. The integration of 463,503 cells from 145 donors resulted in the integrated Human Skin Cell Atlas (iHSCA), forming the basis for the human cell atlas version 1. Additionally, a deep learning-based method, scSEA, was developed for unbiased reference mapping, allowing for the discovery of new cell types.