This code is associated with the paper from  Singhal1 et al., "Cytoprotection by a naturally occurring
variant of ATP5G1 in arctic ground
squirrel neural progenitor cells". eLife, 2020. http://doi.org/10.7554/eLife.55578

Installation Instructions for Dependencies

0) Download and extract / Clone (if you have Git already) project files from github repository
https://github.com/evanmlee/MaLab_spec_subs

1) Python Environment
a) Install conda (Miniconda is sufficient): https://docs.conda.io/projects/conda/en/latest/user-guide/install/
b) Using terminal, navigate to the MaLab_spec_subs installation directory.
c) run the following command to set up an environment with all required packages from the provided environment yml file.
...:MaLab_spec_subs > conda env create --file config/malab_ss.yml
d) Before running project script, activate the malab_ss environment
...:MaLab_spec_subs > source activate malab_ss

2) Install KAlign:
https://github.com/TimoLassmann/kalign/
More recent installation instructions can be found here:
https://github.com/TimoLassmann/kalign/blob/master/README.md
Check KAlign command works (ie no "command not found")
> which kalign
> kalign --help

3) Run test scripts in tests directory (from main spec_subs directory
>source activate malab_ss
(malab_ss) ...:MaLab_spec_subs > python -m unittest discover tests

4) Run main acquisition/filtering/analysis/plotting script
(malab_ss) ...:MaLab_spec_subs > python spec_subs_main.py

With the default configuration file, this should create a subdirectory named cDNAscreen_041020 which will contain
directories for 1) downloaded unfiltered input files (input) 2) filtered record sets and gene specific summary (output)
3) run summary table for all unique substitutions, GS-consensus unique substitutions, filled gene ID tables, plots
(summary)