Skip to main content

A toolbox for working with the Allen Brain Atlas human genetic data

Project description

This package provides a Python interface for working with the Allen Human Brain Atlas (AHBA) microarray expression data.


In 2013, the Allen Institute for Brain Science released the Allen Human Brain Atlas, a dataset containing microarray expression data collected from six human brains. This dataset has offered an unprecedented opportunity to examine the genetic underpinnings of the human brain, and has already yielded novel insight into e.g., adolescent brain development and functional brain organization.

However, in order to be effectively used in most analyses, the AHBA microarray expression data often needs to be (1) collapsed into regions of interest (e.g., parcels or networks), and (2) combined across donors. While this may potentially seem trivial, there are numerous analytic choices in these steps that can dramatically influence the resulting data and any downstream analyses. Indeed, Arnatkevičiūte et al., 2018 ([1]) provided a thorough treatment of this in a recent manuscript, demonstrating how the techniques and code used to prepare the raw AHBA data have varied widely across published reports.

The current Python package, abagen, aims to provide a reproducible pipeline for processing and preparing the AHBA microarray expression data for analysis. If you’d like more information about the package, including how to install it and some example instructions on its use, check out our documentation!

Development and getting involved

This package has been largely developed in the spare time of a single graduate student (@rmarkello) with help from some incredible contributors. While it would be ✨ amazing ✨ if anyone else finds it helpful, given the limited time constraints of graduate school, the current package is not currently accepting requests for new features.

However, if you’re interested in getting involved in the project, we’re thrilled to welcome new contributors! You shouldstart by reading our contributing guidelines and code of conduct. Once you’re done with that, take a look at our issues to see if there’s anything you might like to work on. Alternatively, if you’ve found a bug, are experiencing a problem, or have a question, create a new issue with some information about it!


While this package was initially created in early 2018, many of the current functions in the project were inspired by the workflow laid out in Arnatkevičiūte et al., 2018. As such, if you use this code it would be good to (1) provide a link back to the abagen repository with the version of the code used, and (2) cite their paper:

[1]Arnatkeviciute, A., Fulcher, B. D., & Fornito, A. (2018). A practical guide to linking brain-wide gene expression and neuroimaging data. bioRxiv, 380089.

License Information

This codebase is licensed under the 3-clause BSD license. The full license can be found in the LICENSE file in the abagen distribution.

All trademarks referenced herein are property of their respective holders.

Project details

Release history Release notifications

This version
History Node


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date
abagen-0.0.1-py3-none-any.whl (329.9 kB) Copy SHA256 hash SHA256 Wheel py3
abagen-0.0.1.tar.gz (328.3 kB) Copy SHA256 hash SHA256 Source None

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page