# CoCoMiCo : COoperation and COmpetition in MIcrobial COmmunities
CoCoMiCo aims at characterising the metabolism of microbial communities through genome-scale metabolic networks: it calculates cooperation and competition potentials for the communities.
It has two modes:
* a regular mode: cooperation and competition potentials are computed for a community whose associated genome-scale metabolic networks are located in a directory: (`run` mode)
* a `benchmark` mode: run can be performed systematically for a collection of microbial communities described in a `json` file
CoCoMiCo can be tested on toy data using the following command: `cocomico toys`.
## Install
Required **Python >= 3.7**. The main dependency of CoCoMiCo is an Answer Set Programming (ASP) solver. [Clyngor](https://github.com/Aluriak/clyngor) permits the connection between Python and ASP, whereas [Clyngor_with_clingo](https://github.com/Aluriak/clyngor-with-clingo/) provides the solver binaries in the Python environment. If you work in a conda environment, installing the solvers directly ([clingo](https://anaconda.org/potassco/clingo)) makes it unnecessary to install Clyngor_with_clingo.
```
pip install cocomico
```
or
```
python setyp.py install
```
or after cloning this repository
```
pip install .
```
**If you use CoCoMiCo, please cite:**
Lecomte M, Muller C, Badoual A, Falentin H, Sherman DJ, and Frioux C. 2023. CoCoMiCo: metabolic modelling of cooperation and competition potentials in large-scale bacterial communities.
## Usage
### Single community run
`run` needs the specific architecture as follow:
```
Community_folder
├── species_1.sbml
├── species_4.sbml
├── species_10.sbml
```
Metabolic network file in the community_folder can be in either `.xml` or `.sbml` format. `run` mode creates the `json` community in the appropriate format described in the section **benchmark**.
```
usage: cocomico run [-h] [-folder_path FOLDER_PATH] [-seed_path SEED_PATH] [-output OUTPUT]
optional arguments:
-h, --help show this help message and exit
-i, -folder_path FOLDER_PATH, --folder_path FOLDER_PATH
Directory path of a community composed of sbml or xml files.
-s, -seed_path SEED_PATH, --seed_path SEED_PATH
path of seed file
-o, -output OUTPUT, --output OUTPUT
output path
```
#### Exemple of execution
`
cocomico run -folder_path PATH_COMMUNITIES_FOLDER -seed_path PATH_SEED_FILE -output PATH_OUTPUT
`
### Multiple runs: benchmarking mode
`benchmark` needs the genome-scale metabolic networks used for community construction to be stored in a directory and a json file describing the composition of each sample as follow.
For example:
```
Folder_input
├── communities.json
├── sbml
│ └── species_1.sbml
│ └── species_4.xml
| ..
```
`communities.json`` must be in the following format:
```
{
"com_0" :[
species_1.sbml,
species_4.xml,
species_10.sbml
],
"com_1" :[
species_12.xml,
species_120.sbml
]
}
```
Here, sample `com0` is composed of three species: `species_`, `species_4` and `species_10`.
```
usage: cocomico benchmark [-h] [-json_com JSON_COM] [-seed_path SEED_PATH] [-sbml_path SBML_PATH] [-output OUTPUT]
optional arguments:
-h, --help show this help message and exit
-j, -json_com JSON_COM, --json_com JSON_COM
path of the json file
-s, -seed_path SEED_PATH, --seed_path SEED_PATH
path of seed file
-i, -sbml_path SBML_PATH, --sbml_path SBML_PATH
folder path to find sbml model
-o -output OUTPUT, --output OUTPUT
output path
```
#### Exemple of execution
`
cocomico benchmark -json_com PATH_COMMUNITIES_JSON_FILE -seed_path PATH_SEED_FILE -sbml_path PATH_SBML_DIRECTORY -output PATH_OUTPUT
`
### toys
```
usage: cocomico toys [-h] [-output OUTPUT]
optional arguments:
-h, --help show this help message and exit
-o, -output OUTPUT, --output OUTPUT
output path
```
## Output
In a folder `community_scores`, the output is a json file as follow:
```
{
""metabolite production value (delta)": 31,
"metabolite production value_metric": {
"added value community": 17,
"all individual can produce": 14
},
"cooP": 18.0,
"cooP_metric": {
"number of exchanged metabolites": 8,
"pi producers": 8.5,
"pi consumers": 9.5
},
"reaction production(rho)": 58,
"reaction production_metric": {
"added value comunity": 37
},
"comP": 3.25,
"comP_metric": {
"total number of limited subtrates": 13
},
"bacteria": [
"Com2Org1",
"Com2Org4",
"Com2Org2",
"Com2Org3"
]
}
```
In addition, a `scores.tsv` file is generated, in the output directory, containing all information about the communities:
- `ComP` and `Coop` are respectively the competition and the cooperation potentials.
- `rh` is a score describing the gain of activated reactions in the interacting community with respect to activated reaction in a non-interacting community
- `delt` is a score describing the gain of producible metabolites in the interacting community with respect to activated reaction in a non-interacting community
- `com_siz` describes the size of the corresponding community ie the number of genome-scale metabolic networks
- `nb_exc_cpd` denotes the putative number of metabolic exchanges in the community
- `CooP_producers` and `CooP_consumers` calculate respectively the number of producers and consumers of exchanged metabolites, applying an exponential decrease to the score each time a metabolite is produced (respectively consumed) by more than one member.
| | delta | cooP | rho | comP | com_size | nb_exc_cpd | cooP_producers | cooP_consumers |
|---|-------|------|-----|------|----------|------------|----------------|----------------|
| 0 | 22 | 10.0 | 40 | 2.66 | 3 | 4 | 4.5 | 5.5 |
| 1 | 31 | 18.0 | 58 | 3.25 | 4 | 8 | 8.5 | 9.5 |
# Version
CoCoMiCo version 0.2.1
Raw data
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"description": "# CoCoMiCo : COoperation and COmpetition in MIcrobial COmmunities\n\nCoCoMiCo aims at characterising the metabolism of microbial communities through genome-scale metabolic networks: it calculates cooperation and competition potentials for the communities.\nIt has two modes:\n* a regular mode: cooperation and competition potentials are computed for a community whose associated genome-scale metabolic networks are located in a directory: (`run` mode)\n* a `benchmark` mode: run can be performed systematically for a collection of microbial communities described in a `json` file\n\nCoCoMiCo can be tested on toy data using the following command: `cocomico toys`.\n\n## Install\n\nRequired **Python >= 3.7**. The main dependency of CoCoMiCo is an Answer Set Programming (ASP) solver. [Clyngor](https://github.com/Aluriak/clyngor) permits the connection between Python and ASP, whereas [Clyngor_with_clingo](https://github.com/Aluriak/clyngor-with-clingo/) provides the solver binaries in the Python environment. If you work in a conda environment, installing the solvers directly ([clingo](https://anaconda.org/potassco/clingo)) makes it unnecessary to install Clyngor_with_clingo.\n\n```\npip install cocomico\n```\n\nor\n\n```\npython setyp.py install\n```\n\nor after cloning this repository\n\n```\npip install .\n```\n\n**If you use CoCoMiCo, please cite:**\n\nLecomte M, Muller C, Badoual A, Falentin H, Sherman DJ, and Frioux C. 2023. CoCoMiCo: metabolic modelling of cooperation and competition potentials in large-scale bacterial communities.\n\n## Usage\n\n### Single community run\n\n`run` needs the specific architecture as follow:\n\n```\nCommunity_folder\n\u251c\u2500\u2500 species_1.sbml\n\u251c\u2500\u2500 species_4.sbml\n\u251c\u2500\u2500 species_10.sbml\n```\n\nMetabolic network file in the community_folder can be in either `.xml` or `.sbml` format. `run` mode creates the `json` community in the appropriate format described in the section **benchmark**.\n\n```\nusage: cocomico run [-h] [-folder_path FOLDER_PATH] [-seed_path SEED_PATH] [-output OUTPUT]\n\noptional arguments:\n -h, --help show this help message and exit\n -i, -folder_path FOLDER_PATH, --folder_path FOLDER_PATH\n Directory path of a community composed of sbml or xml files.\n -s, -seed_path SEED_PATH, --seed_path SEED_PATH\n path of seed file\n -o, -output OUTPUT, --output OUTPUT\n output path\n```\n\n#### Exemple of execution\n\n`\ncocomico run -folder_path PATH_COMMUNITIES_FOLDER -seed_path PATH_SEED_FILE -output PATH_OUTPUT\n`\n### Multiple runs: benchmarking mode\n\n`benchmark` needs the genome-scale metabolic networks used for community construction to be stored in a directory and a json file describing the composition of each sample as follow.\nFor example:\n\n```\nFolder_input\n\u251c\u2500\u2500 communities.json\n\u251c\u2500\u2500 sbml\n\u2502 \u2514\u2500\u2500 species_1.sbml\n\u2502 \u2514\u2500\u2500 species_4.xml\n| ..\n```\n\n`communities.json`` must be in the following format:\n\n```\n{\n \"com_0\" :[\n species_1.sbml,\n species_4.xml,\n species_10.sbml\n ],\n \"com_1\" :[\n species_12.xml,\n species_120.sbml\n ]\n}\n\n```\n\nHere, sample `com0` is composed of three species: `species_`, `species_4` and `species_10`.\n\n\n```\nusage: cocomico benchmark [-h] [-json_com JSON_COM] [-seed_path SEED_PATH] [-sbml_path SBML_PATH] [-output OUTPUT]\n\noptional arguments:\n -h, --help show this help message and exit\n -j, -json_com JSON_COM, --json_com JSON_COM\n path of the json file\n -s, -seed_path SEED_PATH, --seed_path SEED_PATH\n path of seed file\n -i, -sbml_path SBML_PATH, --sbml_path SBML_PATH\n folder path to find sbml model\n -o -output OUTPUT, --output OUTPUT\n output path\n\n```\n\n#### Exemple of execution\n\n`\ncocomico benchmark -json_com PATH_COMMUNITIES_JSON_FILE -seed_path PATH_SEED_FILE -sbml_path PATH_SBML_DIRECTORY -output PATH_OUTPUT\n`\n\n\n### toys\n\n```\nusage: cocomico toys [-h] [-output OUTPUT]\n\noptional arguments:\n -h, --help show this help message and exit\n -o, -output OUTPUT, --output OUTPUT\n output path\n```\n\n## Output\n\nIn a folder `community_scores`, the output is a json file as follow:\n\n```\n{\n \"\"metabolite production value (delta)\": 31,\n \"metabolite production value_metric\": {\n \"added value community\": 17,\n \"all individual can produce\": 14\n },\n \"cooP\": 18.0,\n \"cooP_metric\": {\n \"number of exchanged metabolites\": 8,\n \"pi producers\": 8.5,\n \"pi consumers\": 9.5\n },\n \"reaction production(rho)\": 58,\n \"reaction production_metric\": {\n \"added value comunity\": 37\n },\n \"comP\": 3.25,\n \"comP_metric\": {\n \"total number of limited subtrates\": 13\n },\n \"bacteria\": [\n \"Com2Org1\",\n \"Com2Org4\",\n \"Com2Org2\",\n \"Com2Org3\"\n ]\n}\n```\n\nIn addition, a `scores.tsv` file is generated, in the output directory, containing all information about the communities:\n\n- `ComP` and `Coop` are respectively the competition and the cooperation potentials.\n- `rh` is a score describing the gain of activated reactions in the interacting community with respect to activated reaction in a non-interacting community\n- `delt` is a score describing the gain of producible metabolites in the interacting community with respect to activated reaction in a non-interacting community\n- `com_siz` describes the size of the corresponding community ie the number of genome-scale metabolic networks\n- `nb_exc_cpd` denotes the putative number of metabolic exchanges in the community\n- `CooP_producers` and `CooP_consumers` calculate respectively the number of producers and consumers of exchanged metabolites, applying an exponential decrease to the score each time a metabolite is produced (respectively consumed) by more than one member.\n\n| | delta | cooP | rho | comP | com_size | nb_exc_cpd | cooP_producers | cooP_consumers |\n|---|-------|------|-----|------|----------|------------|----------------|----------------|\n| 0 | 22 | 10.0 | 40 | 2.66 | 3 | 4 | 4.5 | 5.5 |\n| 1 | 31 | 18.0 | 58 | 3.25 | 4 | 8 | 8.5 | 9.5 |\n\n\n# Version\nCoCoMiCo version 0.2.1\n",
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