Department of Biostatistics and Bioinformatics, Tampa, FL, USA.
Department of Tumor Biology, Tampa, FL, USA.
Bioinformatics. 2021 Dec 7;37(23):4584-4586. doi: 10.1093/bioinformatics/btab757.
Multiplex immunofluorescence (mIF) staining combined with quantitative digital image analysis is a novel and increasingly used technique that allows for the characterization of the tumor immune microenvironment (TIME). Generally, mIF data is used to examine the abundance of immune cells in the TIME; however, this does not capture spatial patterns of immune cells throughout the TIME, a metric increasingly recognized as important for prognosis. To address this gap, we developed an R package spatialTIME that enables spatial analysis of mIF data, as well as the iTIME web application that provides a robust but simplified user interface for describing both abundance and spatial architecture of the TIME. The spatialTIME package calculates univariate and bivariate spatial statistics (e.g. Ripley's K, Besag's L, Macron's M and G or nearest neighbor distance) and creates publication quality plots for spatial organization of the cells in each tissue sample. The iTIME web application allows users to statistically compare the abundance measures with patient clinical features along with visualization of the TIME for one tissue sample at a time.
spatialTIME is implemented in R and can be downloaded from GitHub (https://github.com/FridleyLab/spatialTIME) or CRAN. An extensive vignette for using spatialTIME can also be found at https://cran.r-project.org/web/packages/spatialTIME/index.html. iTIME is implemented within a R Shiny application and can be accessed online (http://itime.moffitt.org/), with code available on GitHub (https://github.com/FridleyLab/iTIME).
Supplementary data are available at Bioinformatics online.
多重免疫荧光（mIF）染色结合定量数字图像分析是一种新颖且越来越常用的技术，可用于表征肿瘤免疫微环境（TIME）。通常，mIF 数据用于检查 TIME 中免疫细胞的丰度；然而，这并不能捕获免疫细胞在 TIME 中的空间分布模式，而这一指标对于预后越来越重要。为了解决这一差距，我们开发了一个 R 包 spatialTIME，该包可用于分析 mIF 数据的空间分布，以及 iTIME 网络应用程序，该程序提供了一个强大而简化的用户界面，用于描述 TIME 的丰度和空间结构。spatialTIME 包计算单变量和双变量空间统计量（例如 Ripley 的 K、Besag 的 L、Macron 的 M 和 G 或最近邻距离），并为每个组织样本中细胞的空间组织创建出版质量的图。iTIME 网络应用程序允许用户根据患者的临床特征对丰度测量值进行统计比较，并一次可视化一个组织样本的 TIME。
spatialTIME 是用 R 实现的，可以从 GitHub（https://github.com/FridleyLab/spatialTIME）或 CRAN 下载。在 https://cran.r-project.org/web/packages/spatialTIME/index.html 上也可以找到使用 spatialTIME 的详细说明。iTIME 是在 R Shiny 应用程序内实现的，可以在线访问（http://itime.moffitt.org/），代码可在 GitHub（https://github.com/FridleyLab/iTIME）上获得。
补充数据可在 Bioinformatics 在线获得。
