The rtemis ecosystem

rtemis provides a comprehensive console and web-based machine learning and visuzalization platform.

The Python and Julia ports are currently private and will be made available after the rtemis 1.0 release, aiming for a similar API across languages.


The core rtemis API, written in R. rtemis & rtemislive are complementary and interoperable.

For more information on the rtemis package see the online documentation and GitHub repository.


rtemispy is the core rtemis API in Python.


Rtemis.jl is the core rtemis API in Julia.


rtemislive is a comprehensive, modular, and customizable web-based data science platform. It is the graphical user interface for rtemis. It is built using shiny in R.

rtemislive is currently available on the internal UCSF network.

This section provides on an overview of the functionality provided by the package ahead of its public release.


rtemislive provides access to multiple modules which can be toggled before or after launch of the app.

Data Viewer



Network analysis

Map Viewer




Predictive modeling

MRI Viewer

Protein Viewer

PDB Viewer

Built-in help

rtemislive uses tooltips to provide context specific help throughout the UI and also includes builtin help:

List of available modules

  • Data
  • Preprocessing
  • Plot
    • Boxplot
    • Histogram
    • Density
    • Bar plot
    • Scatter
    • Timeseries
    • Volcano
    • Map
  • Heatmap
  • Graph (network) visualization
  • Survival
  • Data Key
  • Table 1
  • Decomposition / Dimensionality reduction
  • Clustering
  • Hypothesis Testing
  • Generalized Linear Models (GLM)
  • mass-GLM
  • Predictive Modeling
    • GLMNET
    • SVM
    • CART
    • Random Forest
    • Gradient Boosting
    • XGBoost