.png){kind=icon}
返回
Optimizing multiplexed imaging experimental design through tissue spatial segregation estimation
.png){kind=icon}
OA
AI
DOI：10.1038/s41592-022-01692-z.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Recent advances in multiplexed imaging methods allow simultaneous detection of dozens of proteins and hundreds of RNAs, enabling deep spatial characterization of both healthy and diseased tissues. Parameters for the design of optimal multiplex imaging studies, especially those estimating how much area has to be imaged to capture all cell phenotype clusters, are lacking. Here, using a spatial transcriptomic atlas of healthy and tumor human tissues, we developed a statistical framework that determines the number and area of fields of view necessary to accurately identify all cell phenotypes that are part of a tissue. Using this strategy on imaging mass cytometry data, we identified a measurement of tissue spatial segregation that enables optimal experimental design. This strategy will enable an improved design of multiplexed imaging studies.
Keyword:
SINGLE
CELLS
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
32.1
论文数:
7.2K
被引数:
12.7W
机构
引用论文
Control of an atomic force microscopy probe during nano-manipulation via the sliding mode method通过滑模方法在纳米操作过程中控制原子力显微镜探针OAAI
OAAI分享收藏分享收藏分享收藏分享收藏In Situ Transcription Profiling of Single Cells Reveals Spatial Organization of Cells in the Mouse Hippocampus单细胞的原位转录谱分析揭示了小鼠海马中细胞的空间组织.png)
NEURONOAAI
NEURONIF15
OAAI分享收藏Rare Cell Detection by Single-Cell RNA Sequencing as Guided by Single-Molecule RNA FISHCELL SYSTEMSOAAI
CELL SYSTEMSIF7.7
OAAI分享收藏
查看更多内容