This repository contains data, code, and results for the manuscript "Standardizing workflows in imaging transcriptomics with the abagen toolbox" by Markello et al. Biorxiv, 2021.
We investigate how variability in processing of the Allen Human Brain Atlas impacts analyses relating gene expression to neuroimaging data and highlight how functionality from the abagen toolbox can help to standardize these workflows.
We've tried to document the various aspects of this repository with a whole bunch of README files, so feel free to jump around and check things out.
Itching to just run the analyses? You'll need to make sure you have installed the appropriate software packages, have access to the HCP, and have downloaded the appropriate data files (check out our walkthrough for more details!). Once you've done that, you can get going with the following:
git clone https://github.com/netneurolab/markello_transcriptome
cd markello_transcriptome
conda env create -f environment.yml
conda activate markello_transcriptome
pip install vibecheck/
make allIf you don't want to deal with the hassle of creating a new Python environment you can create a Singularity image run things in there:
git clone https://github.com/netneurolab/markello_transcriptome
cd markello_transcriptome
bash container/gen_simg.sh
singularity run container/markello_transcriptome.simg make allNote, however, that we don't recommend re-running our analyses in this manner as it will take a very long time to do so! Instead, we refer to our walkthrough for more information on the optimal way to reproduce our results.
If you want a step-by-step through all the methods + analyses take a look at our walkthrough.
Open an issue on this repository and someone will try and get back to you as soon as possible!