整合基因表达和成像数据跨Visium捕获区域与VisiumStitched
Nicholas J Eagles1, Svitlana V Bach1, Madhavi Tippani1
1Lieber Institute for Brain Development, Johns Hopkins Medical Campus, 21205 Baltimore, USA.
bioRxiv : the preprint server for biology
|August 16, 2024
概括
新的visiumStitched R包使研究人员能够结合多个Visium捕获区域进行全面的空间转录分析. 这种工具有助于拼接图像和基因表达数据,允许进行更详细的研究而不会丢失数据.
科学领域:
- 空间转录组学 空间转录组学
- 基因组学就是基因组学.
- 生物信息学是一种生物信息学.
背景情况:
- 视觉 (10x基因组学) 是一个关键的空间转录组学试验.
- 标准捕获区域限制了组织结构分析.
- 现有的软件在合并多个捕获区域方面存在局限性.
研究的目的:
- 开发一种结合多个Visium捕获区域的方法.
- 为了在空间转录学中分析更大的组织部分.
- 为了克服当前多个捕获区合并软件的局限性.
主要方法:
- 开发了R/生物导体包的愿景Stitched.
- 使用斐济 (ImageJ) 来进行图像拼接.
- 构建空间实验R对象与组合数据.
- 为分析创建了一个人造的六角阵列网格.
主要成果:
- 成功地合了部分重叠和相邻的Visium捕获区域.
- visiumStitched可以进行无下游分析,包括空间意识的集群.
- 没有丢弃重叠点的数据.
结论:
- visiumStitched提供了一个灵活的框架,用于多捕获区域空间转录学研究.
- 该套件解决了数据处理方面的挑战,而不会破坏分析工作流程.
- 提供了一个可访问的解决方案,以扩大多捕获区域研究设计.
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