A Roadmap for a Consensus Human Skin Cell Atlas and Single-Cell Data Standardization.

A Roadmap for a Consensus Human Skin Cell Atlas and Single-Cell Data Standardization.
复制标题

DOI:
10.1016/j.jid.2023.03.1679
复制
发表时间:
2023-09
期刊:
The Journal of investigative dermatology
影响因子:
--
通讯作者:
A. Almet;Hao Yuan;Karl Annusver;Raul Ramos;Yingzi Liu;J. Wiedemann;Dara H. Sorkin;N. Landén;E. Sonkoly;M. Haniffa;Qing Nie;B. Lichtenberger;Malte D. Luecken;B. Andersen;L. Tsoi;F. Watt;J. Gudjonsson;M. Plikus;M. Kasper
A. Almet;Hao Yuan;Karl Annusver;Raul Ramos;Yingzi Liu;J. Wiedemann;Dara H. Sorkin;N. Landén;E. Sonkoly;M. Haniffa;Qing Nie;B. Lichtenberger;Malte D. Luecken;B. Andersen;L. Tsoi;F. Watt;J. Gudjonsson;M. Plikus;M. Kasper
中科院分区:
其他
文献类型:
--
作者:
A. Almet;Hao Yuan;Karl Annusver;Raul Ramos;Yingzi Liu;J. Wiedemann;Dara H. Sorkin;N. Landén;E. Sonkoly;M. Haniffa;Qing Nie;B. Lichtenberger;Malte D. Luecken;B. Andersen;L. Tsoi;F. Watt;J. Gudjonsson;M. Plikus;M. Kasper

文献摘要

被引文献

相似文献

单细胞技术已经成为驱动发现的基础和转化调查皮肤病学必不可少的。尽管有大量可用的数据集,但仍然缺乏正常人类皮肤的中央参考图谱,该图谱可以作为皮肤细胞类型、细胞状态及其分子特征的参考资源。对于任何这样的地图集得到广泛的接受,在地图集的构建过程中,许多研究者的参与是必不可少的先决条件。作为人类细胞图谱项目的一部分,我们已经组建了一个皮肤生物网络,以建立一个共识的人类皮肤细胞图谱,并勾勒出实现这一目标的路线图。我们定义了在为图谱选择测序数据集时要考虑的皮肤多样性驱动因素,并列出了皮肤采样过程中可能导致数据空白、阻碍组织处理和计算分析的全面表示和技术考虑的实际障碍,这些障碍的考虑应最大限度地减少细胞类型富集和排除的偏差,并减少批次效应。通过概述Atlas 1.0的目标,我们讨论了它将如何揭示皮肤生物学的新方面。
Single-cell technologies have become essential to driving discovery in both basic and translational investigative dermatology. Despite the multitude of available datasets, a central reference atlas of normal human skin, which can serve as a reference resource for skin cell types, cell states, and their molecular signatures, is still lacking. For any such atlas to receive broad acceptance, participation by many investigators during atlas construction is an essential prerequisite. As part of the Human Cell Atlas project, we have assembled a Skin Biological Network to build a consensus Human Skin Cell Atlas and outline a roadmap toward that goal. We define the drivers of skin diversity to be considered when selecting sequencing datasets for the atlas and list practical hurdles during skin sampling that can result in data gaps and impede comprehensive representation and technical considerations for tissue processing and computational analysis, the accounting for which should minimize biases in cell type enrichments and exclusions and decrease batch effects. By outlining our goals for Atlas 1.0, we discuss how it will uncover new aspects of skin biology.