Name: gtr-tools

Owner: NMDP/Be The Match Bioinformatics Research

Description: null

Created: 2015-08-03 15:53:10.0

Updated: 2015-08-10 17:20:04.0

Pushed: 2015-08-10 17:20:04.0

Homepage: null

Size: 441

Language: Python

GitHub Committers

UserMost Recent Commit# Commits

Other Committers

UserEmailMost Recent Commit# Commits



A set of Python scripts to work with data in the NIH Genetic Testing Registry (GTR).


These programs all run in Python 2.7.


To skip all the steps below, I suggest installing Continuum's Anaconda, which I highly recommend for scientific computing. It already includes all the modules needed to run these scripts, and many others which makes installation of frequently used non-built-in modules easier, it does not affect other python installations on your machine, and the conda package manager is a great way to handle virtual environments.

Traditional, cumbersome way:

  1. If you do not already have Python 2.7, Install Python 2.7 to your computer.
    • If you already have Python 2.7, you will also need pip. This is included starting in Python 2.7.9, so if you have an older version and do not have pip, install pip.
  2. Then clone/download this repository
  3. cd to its location
  4. *then in the terminal enter: pip install -r requirements.txt

*Note: The above steps may require even extra effort to get installed onto osx/linux. lxml may require more dependencies to be installed which can be difficult. Also, tkinter is not in the requirements.txt since it is a built-in but certain versions of OSX/Linux and their shipped Python version do not include it which will require manually installing as well. I suggest just installing Anaconda from the start to avoid complications.


Search provides a GUI program for searching GTR and downloading data. It utilizes the E-utilities.


NGS is a hot topic in bioinformatics and genetic testing. These scripts provide some insight into the growth of NGS in the GTR and best practices for that data.

This work is supported by the National Institutes of Health's National Center for Advancing Translational Sciences, Grant Number U24TR002306. This work is solely the responsibility of the creators and does not necessarily represent the official views of the National Institutes of Health.