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FlydraPandasAnalysis
Orchard
co2_paper_locations
data
fig_1
fig_2
fig_3
fig_4
multicat_analysis
supp_fig_1
supp_fig_10
supp_fig_2
supp_fig_3
supp_fig_4 supp fig 4 Aug 27, 2018
supp_fig_5
supp_fig_6
supp_fig_7
supp_fig_8
supp_fig_9
.gitignore
README.md

README.md

CO2 attraction in Drosophila

This repository contains the software associated with the paper "Drosophila have distinct activity-gated pathways that mediate attraction and aversion to CO2". For a pre-print, see: https://www.biorxiv.org/content/early/2017/12/03/227991

The data (4 TB) will be available upon reasonable request upon formal publication.

Processed data is available through this repository, along with instructions for use, under the folder data/.

This readme assumes working knowledge of Ubuntu and python. This code is not actively maintained. It worked on 2018-08-27 using up-to-date versions of the required software below.

Code and data are licensed under a Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) License.

What you need to run our analysis

You may wish to do all of this in a virtual environment.

The data

If you would like to re-run our analysis, please contact the authors (florisvb@gmail.com). We will make the 4 TB data available through a resilio-sync readonly key.

Once you have the data, you will need to follow the following instructions for making the data accessible to the analysis (below).

Making the data automatically accessible to the analysis

We ran our analysis on several different computers, so to keep track of everything, we created a python package that points to the data and figure template locations. In order to run our analysis, you will need to add your machine and local paths to this repository.

In co2_paper_locations/co2_paper_locations, create a duplicate of data_locations_analysiscavetech_organized.py, e.g. data_locations_yourname.py. Edit the file so that the paths correspond to the data locations on your machine. Next, you will need to create an environmental variable called co2_paper_locations (e.g. type export co2_paper_locations co2_paper_yourname in any terminal window in which you plan to run our code, or add that to your .bashrc). Add an elif statement to the __init__.py file in co2_paper_locations that matches, for example, co2_paper_yourname to data_locations_yourname.py as in the other if and elif statements.

In co2_paper_locations/co2_paper_locations, edit the file figure_template_locations.py, so that the paths match your system.

Install the package (from co2_paper_locations type python setup.py install).

Installing our analysis

In addition to co2_paper_locations, you need to install the following included python packages:

  • Orchard
  • multicat_analysis

Running the analysis

In each "figure" folder there is a make_figureX.py file. Run this file (python ./make_figureX.py) to rerun the analysis and update the associated svg figure files in that directory. You can use this to trace backwards our analysis.

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