1 Introduction

imageTCGA is an R package designed to provide an interactive Shiny application for exploring the TCGA Diagnostic Image Database. This application allows users to filter and visualize metadata, geographic distribution, and other relevant statistics related to TCGA diagnostic images.

This package is part of the Multi-omic Integration of Histopathology Image Analysis working group, which addresses the need for standardized workflows to integrate histopathology image-derived features with genomic and transcriptomic analyses in R/Bioconductor. imageTCGA lays the foundation for a comprehensive platform where pre-extracted image features from Python-based tools from TCGA will be made accessible within R/Bioconductor data structures, streamlining data integration and accelerating research in computational pathology and precision oncology.

2 Installation

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("imageTCGA")

2.1 Setup

Load the package:

library(imageTCGA)

2.2 Run the shiny app

After installing the package, you can run the Shiny application by executing the following command in R:

imageTCGA::imageTCGA()

This will open the application in your default web browser, where you can explore 11,765 diagnostic images from 9,640 patients, filtering them based on various clinical and pathological parameters.

3 Filtering

The application allows filtering by any of the available columns in the dataset. For instance, you can filter for a specific tumor type, such as Ovarian Cancer (107 diagnostic images).

4 R Code

You can generate R code to download the selected images to your local machine by clicking the orange “Generate R Code” button. This utilizes the GenomicDataCommons package.

In the example below, Ovarian Cancer images have been selected:

5 Visualization

5.1 Dotplot

The dot plot visualization allows users to explore gynecological tumors (BRCA, OV, UCS, UCEC). On the left panel, you can select which variables to plot on the x-axis and y-axis.

5.2 Geographic Distribution

The application provides an interactive geographic visualization, displaying the origin of diagnostic images at the center, country, and state level.

For example, in the image below, GBM tumors have been selected. Additionally, summary statistics such as the number of cities and states are reported alongside a bar plot of the state distribution.

6 Session Info

Click here for Session Info

sessionInfo()
#> R version 4.5.0 RC (2025-04-04 r88126)
#> Platform: x86_64-pc-linux-gnu
#> Running under: Ubuntu 24.04.2 LTS
#> 
#> Matrix products: default
#> BLAS:   /home/biocbuild/bbs-3.21-bioc/R/lib/libRblas.so 
#> LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.0  LAPACK version 3.12.0
#> 
#> locale:
#>  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
#>  [3] LC_TIME=en_GB              LC_COLLATE=C              
#>  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
#>  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
#>  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
#> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
#> 
#> time zone: America/New_York
#> tzcode source: system (glibc)
#> 
#> attached base packages:
#> [1] stats     graphics  grDevices utils     datasets  methods   base     
#> 
#> other attached packages:
#> [1] imageTCGA_1.0.0  shiny_1.10.0     BiocStyle_2.36.0
#> 
#> loaded via a namespace (and not attached):
#>  [1] gtable_0.3.6        jsonlite_2.0.0      dplyr_1.1.4        
#>  [4] compiler_4.5.0      BiocManager_1.30.25 bsicons_0.1.2      
#>  [7] promises_1.3.2      tidyselect_1.2.1    Rcpp_1.0.14        
#> [10] leaflet_2.2.2       gridExtra_2.3       tidyr_1.3.1        
#> [13] later_1.4.2         jquerylib_0.1.4     scales_1.3.0       
#> [16] yaml_2.3.10         fastmap_1.2.0       mime_0.13          
#> [19] ggplot2_3.5.2       R6_2.6.1            generics_0.1.3     
#> [22] curl_6.2.2          knitr_1.50          viridis_0.6.5      
#> [25] htmlwidgets_1.6.4   tibble_3.2.1        bookdown_0.43      
#> [28] munsell_0.5.1       bslib_0.9.0         pillar_1.10.2      
#> [31] rlang_1.1.6         cachem_1.1.0        httpuv_1.6.15      
#> [34] xfun_0.52           sass_0.4.10         viridisLite_0.4.2  
#> [37] cli_3.6.4           magrittr_2.0.3      crosstalk_1.2.1    
#> [40] digest_0.6.37       grid_4.5.0          xtable_1.8-4       
#> [43] lifecycle_1.0.4     vctrs_0.6.5         evaluate_1.0.3     
#> [46] glue_1.8.0          codetools_0.2-20    colorspace_2.1-1   
#> [49] purrr_1.0.4         rmarkdown_2.29      tools_4.5.0        
#> [52] pkgconfig_2.0.3     htmltools_0.5.8.1