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---
title: 'GeneNetwork: framework for web-based genetics'
tags:
- bioinformatics
- genetics
- genomics
authors:
- name: Zachary Sloan
orcid: 0000-0002-8099-1363
affiliation: University of Tennessee Health Science Center, USA
- name: Danny Arends
orcid: 0000-0001-8738-0162
affiliation: Humboldt Universityl, Berlin, Germany
- name: Karl W. Broman
orcid: 0000-0002-4914-6671
affiliation: University of Wisconsin, USA
- name: Arthur Centeno
orcid: 0000-0003-3142-2081
affiliation: University of Tennessee Health Science Center, USA
- name: Nick Furlotte
orcid: ?
- name: Harm Nijveen
orcid: 0000-0002-9167-4945
affiliation: Wageningen University, The Netherlands
- name: Lei Yan
orcid: 0000-0001-5259-3379
affiliation: University of Tennessee Health Science Center, USA
- name: Xiang Zhou
orcid: 0000-0002-4331-7599
affiliation: University of Michigan
- name: Robert W. WIlliams
orcid: 0000-0001-8924-4447
affiliation: University of Tennessee Health Science Center, USA
- name: Pjotr Prins
orcid: orcid.org/0000-0002-8021-9162
affiliation: University Medical Center Utrecht, The Netherlands
affiliation: University of Tennessee Health Science Center, USA
date: 29 May 2016
bibliography: paper.bib
---
# Summary
GeneNetwork (GN) is a free and open source (FOSS) framework for web
based genetics that can be deployed anywhere. GN allows biologists to
upload experimental data and map phenotypes interactively against
genotypes using tools, such as R/QTL [@mqm paper] mapping, interval
mapping for model organisms and pylmm; an implementation of FaST-LMM
[@Lippert:2011] which is suitable for human populations and outbred
crosses, such as the mouse diversity outcross. Interactive D3 graphics
are included from R/qtlcharts and presentation-ready figures can be
generated. Recently we have added functionality for phenotype
correlation [@Wang:2016] and network analysis [@WGCNA:2008].
-![Mouse LMM mapping example](qtl2.png)
GN is written in python and javascript and contains a rich set of
tools and libraries that can be written in any computer language. A
full list of included software can be found in
[guix-bioinformatics](https://github.com/genenetwork/guix-bioinformatics/blob/master/gn/packages/genenetwork.scm). To
make it easy to install GN locally in a byte reproducible way,
including all dependencies and a 2GB MySQL test database (the full
database is 160GB and growing), GN is packaged with
[GNU Guix](https://www.gnu.org/software/guix/), as described
[here](https://github.com/genenetwork/genenetwork2/blob/staging/doc/README.org).
GNU Guix deployment makes it feasible to deploy and rebrand GN
anywhere.
# Future work
More mapping tools will be added, including support for Genome-wide
Efficient Mixed Model Association (GEMMA). The
[Biodiallance genome browser](http://www.biodalliance.org/) is being
added as a Google Summer of Code project with special tracks related
to QTL mapping and network analysis. Faster LMM solutions are being
worked on, including GPU support.
A REST interface is being added so that data can be uploaded to a
server, analysis run remotely on high performance hardware, and
results downloaded and used for further analysis. This feature will
allow biologist-programmers to use R and python on their computer and
execute computations on GN enabled servers.
# References
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