转录组
计算生物学
注释
计算机科学
分割
空间分析
生物
生物信息学
人工智能
基因
基因表达
遗传学
地理
遥感
作者
David P. Cook,Kirk B. Jensen,Kellie Wise,Michael J. Roach,Felipe Segato Dezem,Natalie K. Ryan,Michel Zamojski,Ioannis S. Vlachos,Simon Knott,Lisa M. Butler,Jeffrey L. Wrana,Nicholas E. Banovich,Jasmine Plummer,Luciano G. Martelotto
标识
DOI:10.1101/2023.12.13.571385
摘要
Abstract Spatial transcriptomics is a rapidly evolving field, overwhelmed by a multitude of technologies. This study aims to offer a comparative analysis of datasets generated from leading in situ imaging platforms. We have generated spatial transcriptomics data from serial sections of prostate adenocarcinoma using the 10x Genomics Xenium and NanoString CosMx SMI platforms. Additionally, orthogonal single-nucleus RNA sequencing (snRNA-seq) was performed on the same FFPE tissue to establish a reference for the tumor’s transcriptional profiles. We assessed various technical aspects, such as reproducibility, sensitivity, dynamic range, cell segmentation, cell type annotation, and congruence with single-cell profiling. The practicality of assessing cellular organization and biomarker localization was evaluated. Although fewer genes are measured (CosMx: 960, Xenium: 377, with an overlap of 125), Xenium consistently demonstrates higher sensitivity, a broader dynamic range, and better alignment with single-cell reference profiles. Conversely, CosMx’s out-of-the-box segmentation outperformed Xenium’s, resulting in noticeable transcript misassignment in Xenium within certain tissue areas. However, the impact of this on the cells’ transcriptional profile was minimal. Together, this comprehensive comparison of two leading commercial platforms for spatial transcriptomics provides essential metrics for assessing their performance, offering invaluable insights for future research and technological advancements in this dynamic field.
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