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Installation

Two general things are need for program usage:

  1. Environment setup
  2. Input file preparation

Setting up your environment

In the terminal, go to directory of choice and clone this repo:

git clone https://github.com/acolorado1/DietMicrobeNet.git       # clone repo
cd DietMicrobeNet                                                # move into this project directory

Create environment with yaml file provided:

conda env create -f DMnet_env.yaml                              # create environment
conda activate DietMicrobeNet                                   # activate environment 
pip install -e .                                                # set up directory structure

Download FooDB and HMDB database information

For the following scripts to run you will need four files taken from FooDB and HMDB located in a public drive, and one file for all food item compounds found in FooDB.

To do this run: 

wget 'https://olucdenver-my.sharepoint.com/:x:/g/personal/angelasofia_burkhartcolorado_cuanschutz_edu/ESXx7vpypQFOt4iVv6x-ErkBykpAVS1fppQjYZkrxkDnAA?download=1' -O Data/CompoundExternalDescriptor.csv
wget 'https://olucdenver-my.sharepoint.com/:x:/g/personal/angelasofia_burkhartcolorado_cuanschutz_edu/EYJUYQWmY9VDlYZIAXpzpvEBzhrnViFZQjrikXIla_aPPg?download=1' -O Data/Content.csv
wget 'https://olucdenver-my.sharepoint.com/:x:/g/personal/angelasofia_burkhartcolorado_cuanschutz_edu/EXyRAlYs1htNlcwz5T67BxQBGO7HfOjmfIBlkOydM0BIAw?download=1' -O Data/Food.csv
wget 'https://olucdenver-my.sharepoint.com/:x:/g/personal/angelasofia_burkhartcolorado_cuanschutz_edu/EbY2fD3JTcNLomKFqQhY5jABAXN-60A80PmkngRynazocg?download=1' -O Data/hmdb.csv
wget 'https://olucdenver-my.sharepoint.com/:x:/g/personal/angelasofia_burkhartcolorado_cuanschutz_edu/EZ1pyHd616RFkR9zG6kenuoBhZDroHYTbaGmEfwpxFOHLg?download=1' -O Data/AllFood/food_meta.csv

Needed Files for Input

There are three types of files that are needed to run the program:

  1. File containing a list of KOs that were found in a sample
  2. File containing KO metadata
  3. File containing a list of food items that combined represent diet

List of KOs

  • Needs to be named noquote_ko.txt
  • File needs to have no quotes or commas

Example of the file: 

K00001
K00002
K00003
K00004
K00005
K00008

KO Metadata

  • Needs to be named ko_taxonomy_abundance.csv
  • Should have three columns "KO", "taxonomy", and a column representing read abundance (in this case it is "Abundance_RPKs")
  • ONLY the read abundance column is mutable meaning this CSV must have these EXACT column names for KO and taxonomy
  • If you do not have taxonomy or abundance information leave the column blank, downstream process will eliminate empty values

Example of the file: 

"KO","taxonomy","Abundance_RPKs"
"K00001","g__Bifidobacterium.s__Bifidobacterium_bifidum",30.025907407
"K00001","g__Bifidobacterium.s__Bifidobacterium_longum",0
"K00001","unclassified",0
"K00002","g__Blautia.s__Blautia_obeum",41.8831170812
"K00002","g__Blautia.s__Blautia_sp",0
"K00002","g__Blautia.s__Blautia_sp_AF19_10LB",0
"K00002","unclassified",0

Food items

  • These are typically downloaded in the second step of this workflow (see 2. Find Food Items)
  • Named either foodb_foods_dataframe.csv or kegg_organisms_dataframe.csv
  • If you want to include all possible food items you can use Data/AllFood/food_meta.csv (see 2. Find Food Items)