微阵列集成空间转录组学(MIST)可负担得起和强大的数字病理学。

IF 3.5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Juwayria, Priyansh Shrivastava, Kaustar Yadav, Sourabh Das, Shubham Mittal, Sunil Kumar, Deepali Jain, Prabhat Singh Malik, Ishaan Gupta
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引用次数: 0

摘要

10X Visium是一种流行的空间转录组学(ST)方法,由于其高成本和每张幻灯片的样本使用限制,其采用受到限制。为了解决这些问题,我们提出了微阵列集成空间转录组学(MIST),将传统的组织微阵列(TMA)与Visium相结合,使用激光切割和3D打印来提高载玻片的吞吐量。我们的设计便于在个别实验室进行独立复制和定制,以满足特定的实验需求。我们提供从设计tma到库准备步骤的逐步指南。我们展示了MIST相对于Visium和GeoMx纳米管柱的成本效益和技术优势。我们还介绍了“AnnotateMap”,这是一种新的计算工具,用于有效分析通过MIST处理的多个roi。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Microarray integrated spatial transcriptomics (MIST) for affordable and robust digital pathology.

10X Visium, a popular Spatial transcriptomics (ST) method, faces limited adoption due to its high cost and restricted sample usage per slide. To address these issues, we propose Microarray Integrated Spatial Transcriptomics (MIST), combining conventional tissue microarray (TMA) with Visium, using laser-cutting and 3D printing to enhance slide throughput. Our design facilitates independent replication and customization in individual labs to suit specific experimental needs. We provide a step-by-step guide from designing TMAs to the library preparation step. We demonstrate MIST's cost-effectiveness and technical benefits over Visium and GeoMx Nanostring. We also introduce 'AnnotateMap', a novel computational tool for efficient analysis of multiple ROIs processed through MIST.

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来源期刊
NPJ Systems Biology and Applications
NPJ Systems Biology and Applications Mathematics-Applied Mathematics
CiteScore
5.80
自引率
0.00%
发文量
46
审稿时长
8 weeks
期刊介绍: npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology. We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.
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