SYNULATOR

Synulator (Simulation for Synthetic Lethality) is a tool for simulating genetic interaction screen data, modeling fitness effects, and predicting synergistic genetic interactions.

Dependencies

To run this software, Python>=3.10.1 is required.

Software dependencies:

• numpy==2.0.2
• pandas==2.2.3
• scipy==1.13.1

Installation

1. Clone the repository into a directory on your computer and cd into the root directory of the SYNULATOR package.

git clone https://github.com/hart-lab/SYNULATOR.git
cd SYNULATOR

2. Optional but recommended, create and start a virtual environment for the tool with:

python3 -m venv syenv
source syenv/bin/activate

To exit the environment later, run deactivate in the command line.

3. Install using the setup.py file with:

pip3 install .

4. Verify installation:

synulator -h

You should see the following:

usage: synulator [-h] -o OUTPUT [--num_total_genes NUM_TOTAL_GENES] [--num_fitness_genes NUM_FITNESS_GENES] [--mu_k_wt MU_K_WT] [--mu_k_fitness_min MU_K_FITNESS_MIN] [--mu_k_fitness_max MU_K_FITNESS_MAX] [--genetic_interaction_frequency GENETIC_INTERACTION_FREQUENCY] [--genetic_interaction_fitness_min GENETIC_INTERACTION_FITNESS_MIN] --genetic_interaction_fitness_max GENETIC_INTERACTION_FITNESS_MAX] [--wt_gi_multiplier WT_GI_MULTIPLIER] [--num_guides NUM_GUIDES] [--sigma_k SIGMA_K] [--time TIME] [--transduction_depth TRANSDUCTION_DEPTH] [--median_read_depth MEDIAN_READ_DEPTH] [--overdispersion_param OVERDISPERSION_PARAM] [--pseudocount PSEUDOCOUNT] [--seed SEED]

Simulate genetic interaction screen data.

Quick Usage Example

synulator -o ./test.txt --num_total_genes 300 --num_fitness_genes 50 --time 6

Required Arguments

Argument	Description
-o, --output	Output file path for simulation results

Optional Arguments

Argument	Description	Default
--num_total_genes	Total number of genes in the simulated library	200
--num_fitness_genes	Number of fitness genes (non-wildtype)	50
--mu_k_wt	Mean fitness of wildtype genes	1.0
--mu_k_fitness_min	Minimum fitness for a fitness gene	0.2
--mu_k_fitness_max	Maximum fitness for a fitness gene	1.0
--genetic_interaction_frequency	Probability of a genetic interaction occurring	0.01
--genetic_interaction_fitness_min	Minimum fitness for genetic interaction	0.2
--genetic_interaction_fitness_max	Maximum fitness for genetic interaction	1.0
--wt_gi_multiplier	Multiplier to reduce genetic interaction frequency in wildtype genes	0.1
--num_guides	Number of guides targeting each gene	4
--sigma_k	Standard deviation of fitness means	0.03
--time	Number of cell doublings (time steps)	8
--transduction_depth	Initial cell transduction depth	500
--median_read_depth	Median sequencing read depth	500
--overdispersion_param	Overdispersion parameter (must be 0-1)	0.5
--pseudocount	Pseudocount added to avoid division by zero	1
--seed	Seed value for reproducibility	None