School of Mathematics and Statistics, The University of Sydney, Camperdown, NSW 2006, Australia.
Charles Perkins Centre, The University of Sydney, Camperdown, NSW 2006, Australia.
Bioinformatics. 2023 Sep 2;39(9). doi: 10.1093/bioinformatics/btad550.
Imaging-based spatial transcriptomics (ST) technologies have achieved subcellular resolution, enabling detection of individual molecules in their native tissue context. Data associated with these technologies promise unprecedented opportunity toward understanding cellular and subcellular biology. However, in R/Bioconductor, there is a scarcity of existing computational infrastructure to represent such data, and particularly to summarize and transform it for existing widely adopted computational tools in single-cell transcriptomics analysis, including SingleCellExperiment and SpatialExperiment (SPE) classes. With the emergence of several commercial offerings of imaging-based ST, there is a pressing need to develop consistent data structure standards for these technologies at the individual molecule-level.
To this end, we have developed MoleculeExperiment, an R/Bioconductor package, which (i) stores molecule and cell segmentation boundary information at the molecule-level, (ii) standardizes this molecule-level information across different imaging-based ST technologies, including 10× Genomics' Xenium, and (iii) streamlines transition from a MoleculeExperiment object to a SpatialExperiment object. Overall, MoleculeExperiment is generally applicable as a data infrastructure class for consistent analysis of molecule-resolved spatial omics data.
The MoleculeExperiment package is publicly available on Bioconductor at https://bioconductor.org/packages/release/bioc/html/MoleculeExperiment.html. Source code is available on Github at: https://github.com/SydneyBioX/MoleculeExperiment. The vignette for MoleculeExperiment can be found at https://bioconductor.org/packages/release/bioc/html/MoleculeExperiment.html.
基于成像的空间转录组学 (ST) 技术已经实现了亚细胞分辨率,能够在其天然组织环境中检测单个分子。与这些技术相关的数据有望为理解细胞和亚细胞生物学提供前所未有的机会。然而,在 R/Bioconductor 中,现有的计算基础设施缺乏用于表示此类数据的能力,特别是缺乏用于汇总和转换数据的能力,而这些数据对于单细胞转录组学分析中现有的广泛采用的计算工具,包括 SingleCellExperiment 和 SpatialExperiment (SPE) 类,非常重要。随着基于成像的 ST 的几个商业产品的出现,迫切需要在单个分子水平上为这些技术开发一致的数据结构标准。
为此,我们开发了 MoleculeExperiment,这是一个 R/Bioconductor 软件包,它 (i) 在分子水平存储分子和细胞分割边界信息,(ii) 跨不同基于成像的 ST 技术标准化此分子级别的信息,包括 10× Genomics 的 Xenium,以及 (iii) 简化从 MoleculeExperiment 对象到 SpatialExperiment 对象的转换。总体而言,MoleculeExperiment 通常适用于一致分析分子分辨率空间组学数据的基础数据基础设施类。
MoleculeExperiment 软件包可在 Bioconductor 上公开获取,网址为 https://bioconductor.org/packages/release/bioc/html/MoleculeExperiment.html。源代码可在 Github 上获取,网址为:https://github.com/SydneyBioX/MoleculeExperiment。MoleculeExperiment 的简介可在 https://bioconductor.org/packages/release/bioc/html/MoleculeExperiment.html 上获取。