小柯机器人

新加坡基因组研究所Shyam Prabhakar等研究人员合作发现，BANKSY可统一细胞分型和组织域分割并用于可扩展的空间组学数据分析。该项研究成果于2024年2月27日在线发表在《自然—遗传学》上。

研究人员表示，空间组学数据通过聚类来定义细胞类型和组织域。

研究人员提出的“利用邻域核和空间标准构建聚合”（BANKSY）算法将这两个空间聚类问题统一起来，将细胞嵌入其自身和本地邻域转录组的乘积空间，分别代表细胞状态和微环境。在对不同的RNA（成像、测序）和蛋白质（成像）数据集进行测试时，BANKSY的空间特征增强策略提高了这两项任务的性能。BANKSY揭示了小鼠大脑中意想不到的依赖于微环境的细胞状态，在领域分割和细胞分型基准测试中的表现优于其他竞争方法。

BANKSY还可用于空间转录组学数据的质量控制和空间感知批次效应校正。重要的是，与现有方法相比，它的速度更快，可扩展性更强，可处理数百万个细胞数据集。总之，BANKSY为分析空间解析的组学数据提供了一个准确、具有生物学动机、可扩展且用途广泛的框架。

附：英文原文

Title: BANKSY unifies cell typing and tissue domain segmentation for scalable spatial omics data analysis

Author: Singhal, Vipul, Chou, Nigel, Lee, Joseph, Yue, Yifei, Liu, Jinyue, Chock, Wan Kee, Lin, Li, Chang, Yun-Ching, Teo, Erica Mei Ling, Aow, Jonathan, Lee, Hwee Kuan, Chen, Kok Hao, Prabhakar, Shyam

Issue&Volume: 2024-02-27

Abstract: Spatial omics data are clustered to define both cell types and tissue domains. We present Building Aggregates with a Neighborhood Kernel and Spatial Yardstick (BANKSY), an algorithm that unifies these two spatial clustering problems by embedding cells in a product space of their own and the local neighborhood transcriptome, representing cell state and microenvironment, respectively. BANKSY’s spatial feature augmentation strategy improved performance on both tasks when tested on diverse RNA (imaging, sequencing) and protein (imaging) datasets. BANKSY revealed unexpected niche-dependent cell states in the mouse brain and outperformed competing methods on domain segmentation and cell typing benchmarks. BANKSY can also be used for quality control of spatial transcriptomics data and for spatially aware batch effect correction. Importantly, it is substantially faster and more scalable than existing methods, enabling the processing of millions of cell datasets. In summary, BANKSY provides an accurate, biologically motivated, scalable and versatile framework for analyzing spatially resolved omics data.

DOI: 10.1038/s41588-024-01664-3

Source: https://www.nature.com/articles/s41588-024-01664-3

Nature Genetics：《自然—遗传学》，创刊于1992年。隶属于施普林格·自然出版集团，最新IF：41.307
官方网址：https://www.nature.com/ng/
投稿链接：https://mts-ng.nature.com/cgi-bin/main.plex