3D computational reconstruction of tissues with hollow spherical morphologies using single-cell gene expression data.
3D computational reconstruction of tissues with hollow spherical morphologies using single-cell gene expression data.
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DOI：
10.1038/nprot.2015.022
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发表时间：
2015-03
期刊：
影响因子：
14.8
通讯作者：
Heller S
中科院分区：
文献类型：
--
作者：
Durruthy-Durruthy R;Gottlieb A;Heller S
单细胞基因表达分析有助于更好地理解各种模型系统中的转录异质性，包括用于发育，癌症和干细胞生物学研究的那些。如今，技术进步促进了以高通量格式生成大型基因表达数据集。需要策略来有针对性地将这些信息在组织结构相关的上下文中可视化，以便改进数据分析并帮助得出有意义的结论。在这里，我们描述了一种方法，利用组织源的空间特性，使重建的空心球形组织和器官的单细胞基因表达数据在三维空间。为了证明我们的方法，我们使用的细胞的小鼠耳囊肿和肾囊作为例子。该协议提出了一个简单的计算表达式分析工作流程，并在MATLAB和R统计计算和图形软件平台上实现。使用标准台式PC或Mac进行典型实验的动手时间可能不到1小时。
Single-cell gene expression analysis has contributed to a better understanding of the transcriptional heterogeneity in a variety of model systems, including those used in research in developmental, cancer, and stem cell biology. Nowadays, technological advances facilitate the generation of large gene expression datasets in high-throughput format. Strategies are needed to pertinently visualize this information in a tissue–structure related context, so as to improve data analysis and aid the drawing of meaningful conclusions. Here we describe an approach that utilizes spatial properties of the tissue source to enable the reconstruction of hollow sphere–shaped tissues and organs from single-cell gene expression data in three-dimensional space. To demonstrate our method, we used cells of the mouse otocyst and the renal vesicle as examples. This protocol presents a straightforward computational expression analysis workflow and is implemented on the MATLAB and R statistical computing and graphics software platforms. Hands-on time for typical experiments can be less than 1 h using a standard desktop PC or Mac.