AEGIS

Aging of Evolving Genomes In Silico (AY-jis, /eɪd͡ʒɪs/)

Numerical model for life history evolution of age-structured populations under customizable ecological scenarios.

How to install

We recommend that you install aegis-sim from PyPI into a virtual environment.

$ pip install aegis-sim

If you will using the jupyter notebook visualization script, you might need to run jupyter nbextension enable --py widgetsnbextension to activate widgets.

# Unix/macOS
python3 -m venv aegis-venv
. aegis-venv/bin/activate
python3 -m pip install aegis-sim

# Windows
python -m venv aegis-venv
.\aegis-venv\Scripts\activate
python -m pip install aegis-sim

# Unix/macOS
git clone git@github.com:valenzano-lab/aegis.git
cd aegis
make install_dev

To check if installation is successful, run aegis -h. If it is, the output will contain Aging of Evolving Genomes In Silico; if not, it will say aegis: command not found.

How to run

1. Create a configuration file

   Before running a custom AEGIS simulation, you must create a configuration file (in YAML format) which will contain your custom parameter values. List of modifiable parameters, and all relevant details can be found in the wiki. Default parameter values are set in the file default.yml.

   An example of a YAML file:

   # custom.yml
   
   RANDOM_SEED_: 42
   STAGES_PER_SIMULATION_: 10000
   MAX_LIFESPAN: 50

2. Start the simulation

   $ aegis {path/to/file}.yml # In this case, `aegis custom.yml`

3. Inspect the output

   Output files will be created in the {path/to/file} directory (in this case, in the custom directory) which will have the following structure:

   {path/to/file}/
       progress.log
       {ecosystem-number}/
           output-summary.json
           snapshots/
               demography/
                   {stage}.feather
                   ...
               genotypes/
                   {stage}.feather
                   ...
               phenotypes/
                   {stage}.feather
           visor/
               genotypes.csv
               phenotypes.csv
               spectra/
                   age_at_birth.csv
                   age_at_end_of_sim.csv
                   age_at_genetic.csv
                   age_at_overshoot.csv
                   age_at_season_shift.csv
                   cumulative_ages.csv

   Detailed description of the content and format of output files can be found in the wiki.

Related articles

• An In Silico Model to Simulate the Evolution of Biological Aging (2016)
• AEGIS: An In Silico Tool to model Genome Evolution in Age-Structured Populations (2019)

Authors

• Martin Bagić (v2): email, github
• Dario Valenzano (v1, v2): github
• Arian Šajina (v1): github
• William Bradshaw (v1): github