Repository for code associated with the preprint:
A macroecological perspective on genetic diversity in the human gut microbiome.
All code was written in Python 2.7. Details of the conda environment can be found in environment.yml. Set up the repo under a folder named Github: ~/GitHub/snv_prevalence/.
All the commands to reprocess the data are called in run_everything.sh. This script contains commands for all data processing and analyses, including MIDAS. You will need to rework the paths in the scripts listed in run_everything.sh to get it working on your machine, including moving all HMP fastq files into ~/GitHub/snv_prevalence/data/SRA_files/. All bash scripts are written to be run on a cluster. I do not recommend running them on your local machine.
Python scripts in run_everything.sh that are marked for figure generation can be run on a local machine. These scripts require the processed data.