Oris

Oris — Boolean Logic-Based Estimation of Synergy Scores — is a module built on top of BooLEVARD for computing Bliss-type synergy scores from Boolean model ensembles produced with Gitsbe. Within Trafikk, Oris operates on Celios-calibrated model ensembles to assess the impact of single and combined perturbations defined with Drexpa.

In addition to synergy scoring, Oris can also be used as a generic path-based signal transduction quantifier: it measures the propagation of activity from input nodes to selected output nodes in Boolean models, which can serve as a proxy for cell viability or functional output.

---

Features

• Synergy Mode (--mode synergies): computes Bliss synergy excess for drug pair perturbations.
• Count Paths Mode (--mode countpaths): quantifies signal propagation toward all Boolean nodes.
• Full Mode (--mode full): runs both synergy and count-paths analyses in a single execution.

---

Requirements

• Python 3.10+
• BooLEVARD
• mpi4py
• pandas
• numpy

Note: Oris is designed to run on high-performance computing (HPC) systems equipped with:

• SLURM workload manager for job scheduling
• An MPI implementation (e.g. OpenMPI or Intel MPI)

---

Installation

pip install git+https://github.com/druglogics/oris.git

---

Quick Start

oris --zips /path/to/zips --sampling 10 --mode synergies

Oris requires three mandatory parameters:

Parameter	Description
--zips	Path to the directory containing input ZIP files
--sampling	Number of models to sample from the Gitsbe-generated ensemble
--mode	Operational mode: synergies, countpaths, or full

Optional parameters include --config (custom TOML configuration file), --skip-initial (skip media and initial conditions), --timeout-sampling, --timeout-paths, --dry-run, and --verbose.

---

Configuration

Oris uses a TOML configuration file to control its execution environment, HPC scheduling, and simulation parameters. If no file is provided via --config, Oris falls back to a built-in default.

The configuration file has three sections:

1. [slurm] — HPC scheduling directives
2. [env] — Software environment setup
3. [oris] — Simulation parameters

Example:

[slurm]
partition       = "CPUQ"
nodes           = 18
ntasks_per_node = 14
time            = "24:00:00"
auto_submit     = true

[env]
preamble = """
module load intel/2024a
module load Python/3.12.3-GCCcore-13.3.0
"""

[oris]
default_sampling = 10
media_targets    = ["EGFR", "IGF1R", "MET"]
timeout_sampling = 300
timeout_paths    = 600

---

Outputs

Oris augments the input ZIP files with a Results/ directory containing:

Mode	Output files
synergies	PathCounts, SynergyExcess
countpaths	PathCountsFull
full	PathCounts, PathCountsFull, SynergyExcess

---

License

This project is licensed under the GNU General Public License v3.0. See LICENSE for details.