An interactive web portal for exploring immuno-oncology data
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Failed to load latest commit information.
data add context text in TIL map description Nov 2, 2018
iatlas change scripts for travis testiung Aug 30, 2018
pages fix text case in headers Sep 30, 2018
DEPENDENCIES first working version Sep 23, 2018
LICENSE Create LICENSE May 17, 2018 updated readme to remind users to install development plotly Sep 14, 2018
_DESCRIPTION hide DESCRIPTION file for now to prevent shinyapps deploy errors Sep 30, 2018
configuration.yaml redid how plot colors are handled Nov 2, 2018
footer.html edits to about page and email added to Contact us Apr 4, 2018
global.R refactor tests owrking, immune features slow Oct 25, 2018
run_tests.R change scripts for travis testiung Aug 30, 2018


Shiny-iAtlas is an interactive web portal that provides multiple analysis modules to visualize and explore immune response characterizations across cancer types. The app is hosted on at and can also be accessed via the main CRI iAtlas page at

The portal is built entirely in R and Shiny using the RStudio development environment. Layout and interactivity within the portal are achieved by heavy use of the following packages:

  • shinydashboard
  • plotly
  • crosstalk

Violin plots are not available in the current version of plotly in CRAN; need to use development version from GitHub (e.g., To install the development version:


Other data transformation and formatting operations, as well as many other general application tasks, are supported by a variety of packages in the tidyverse. For a full list of dependencies (as generated by rsconnect::appDependencies()), see the DEPENDENCIES file.


Input data for the Shiny-iAtlas portal were accessed from multiple remote sources, including Synapse, the ISB Cancer Genomics Cloud, and Google Drive. For convenience, we have created locally cached versions of dataframe objects as feather files:

  • fmx_df.feather
  • feature_df.feather
  • feature_method_df.feather
  • im_direct_relationships.feather
  • im_potential_factors.feather
  • im_expr_df.feather
  • sample_group_df.feather


While many of the results presented in tables and plots are taken directly from IRWG data (including the main feature matrix and various feature and group annotations), we compute some values internally. Unless otherwise noted, the following methods/tools were used to compute summary statistics:

Correlation — Spearman's rank-order correlation:

stats::cor(x, y, method = "spearman", use = "pairwise.complete.obs")

Concordance Index (CI):

Concordance indexes for survival endpoints with respect to different immune readouts were computed using a custom package developed by Tai-Hsien Ou Yang at Columbia University. The concordanceIndex package includes a single synonymous function that can be used as follows:

concordanceIndex::concordanceIndex(predictions, observations)

... where predictions and observations are numerical vectors of the same length.

The concordanceIndex package can be installed from GitHub using devtools:


Local Shiny-iAtlas Session

To run the app locally, clone this repository and use the following command in the shiny-iatlas directory: