Skip to content


Switch branches/tags

Latest commit


Git stats


Failed to load latest commit information.
Latest commit message
Commit time

Epiviz Feed Computation Server

This repository sets up the backend computational system for automatic statistical analysis in Epiviz Feed. It is implemented in Python. Each instance of the server is configured using a JSON file which lists datasets to be included in the computations. The statistical analysis methods are designed as modules in this python package that implement a specific API that allows them to be called by the computation server. New modules can be included by the analysts for their specific analyses.

Install Python package Dependencies

The current repos uses Python 2. 7. The requirements.txt contains all the dependencies and can be installed through pip by

pip install -r requirements.txt

Configuration File (JSON format)

The Epiviz Feed computational system uses a JSON configuration file to setup statistical tests and datasets for analysis. This JSON file contains

  • Measurements/datasets
  • list of statistical tests
  • Statistical threshold (e.g., p-value) to filter results (defaults to 0.1) and
  • Annotations/Links to the data (this information is displayed in the "information button" from the interface)

An example json file is setup in the repository. This configuration contains dataset hosted at University of Maryland and example computations.

Setup datasets

Epiviz data provider is a python package that allows users to query genomic data stored in files or database. To setup an instance of the data provider, visit

Implement new statistical tests

The statistical analysis methods are modules and independent. The base of all currently implemented statistical methods lies in the StatMethod class and developers can extend this class to implement customized computational modules. The module also needs to implement a compute function that performs the statistical analysis in a specific genomic region.

Running the server

Epiviz Feed uses websockets to communicate between the user interface and the computational server. To run the server, use

python (make sure you update the configuration file name in this script)

Epiviz Feed Application

This (Epiviz Feed Polymer ) repository contains the code and instructions for running the web interface. You have to run both to have a fully functional application.


backend computational support for epiviz feed results






No packages published