lsbnb/triad repository overview

TRIAD (Multimodal T-Cell Epitope Prioritization and Autonomous Immunology AI Agent Platform) is an integrated, high-performance web platform designed for rapid CD8+ T-cell epitope discovery, antigen presentation prediction, 3D pMHC structural modeling, physicochemical T-cell immunogenicity scoring, and global population coverage analysis.

Developed by the Laboratory of Systems Biology and Bioinformatics (LSBNB), Institute of Information Science, Academia Sinica, Taiwan.

⁠⚡ Key Features

• High-Throughput Epitope Discovery: Supports raw peptide lists or full-length protein FASTA sequences with configurable k-mer sliding windows (8–14 aa).
• MHC-I Antigen Presentation ANN: Integrates NetMHCpan-4.2 trained on over 1,000,000 mass spectrometry eluted ligands (MS-EL) and quantitative binding affinity (BA) datasets.
• Physicochemical T-Cell Immunogenicity: Implements Calis et al. (2013) log-odds scoring model based on position-weighted amino acid properties at TCR-contact positions (positions 4–8).
• Physicochemical TCR Contact Feature Evaluation: Evaluates T-cell receptor contact amino acid properties to predict immune activation potential and candidate concordance.
• Population-Aware Coverage: Computes non-redundant population coverage across global and regional cohorts (Taiwan, East Asia, Europe, World).
• Multimodal Candidate Tiering: Automatically categorizes candidates into Tier 1 (High priority), Tier 2 (Secondary), and Tier 3 based on a harmonized 4-dimensional Composite Priority Index.
• In-Memory RAM Disk Acceleration Engine: Parallel multi-core batch processing using /dev/shm for zero-disk-latency temporary sequence ingestion.

⁠🚀 Quick Start Guide

⁠1. Pull Image from Docker Hub

docker pull lsbnb/triad:latest
# or
docker pull lsbnb/mhcpan_shell:latest

⁠2. Launch Container with Port Mapping 5001:5001

⁠Option A: Command Line Interface (CLI)

Run the container mapping host port 5001 to container port 5001:

docker run -d \
  --name triad_app \
  -p 5001:5001 \
  --restart unless-stopped \
  lsbnb/triad:latest

Open your browser and navigate to:
👉 http://localhost:5001 (or http://127.0.0.1:5001)

⁠Option B: Docker Desktop Graphical Interface (Windows / macOS GUI Users)

If you use Docker Desktop GUI:

1. Click Run on the lsbnb/triad:latest image.
2. Expand Optional settings → Ports.
3. Fill in 5001 in the Host port field (which maps to :5001/tcp).
4. Click Run.

![Docker Desktop Host Port 5001 Setup]

⁠🔑 NetMHCpan-4.2 Academic Licensing & Setup Guide

netMHCpan-4.2 is academic-licensed software copyrighted by DTU Health Tech (Technical University of Denmark). Its academic license explicitly prohibits third-party redistribution of binary executables and model parameters ("not give the program to third parties").

For legal compliance, the public Docker image (lsbnb/triad) ships as a clean application shell without pre-bundled DTU files. Each user must obtain their own copy directly from DTU.

⁠Step 1: Request Linux Package from DTU

1. Visit the Official DTU Download Portal⁠.
2. Request the Linux tarball package (filename format: netMHCpan-4.2.Linux.tar.gz).

⁠Step 2: Configure Container (Choose Method 1 or Method 2)

⁠Method 1: Host Directory Volume Mount (Server / CLI)

Extract the package on your host machine and mount it to /opt/netMHCpan-4.2:

# 1. Unpack DTU package on host
tar -xzvf netMHCpan-4.2.Linux.tar.gz

# 2. Start container with volume mount and port mapping 5001:5001
docker run -d \
  --name triad_app \
  -p 5001:5001 \
  -v /dev/shm:/dev/shm \
  -v "$(pwd)/netMHCpan-4.2:/opt/netMHCpan-4.2" \
  lsbnb/triad:latest

⁠Method 2: Web Upload Wizard (No Terminal Access Needed)

1. Start the container with port mapping 5001:5001:

   docker run -d --name triad_app -p 5001:5001 lsbnb/triad:latest
   

   Copy
2. Open http://localhost:5001/setup in your web browser.
3. Upload your netMHCpan-4.2.Linux.tar.gz file.
4. Confirm license compliance and click Upload & Install. The platform automatically extracts, verifies, tests, and activates the engine.

⁠🐳 Docker Compose Deployment

Create a docker-compose.yml file:

version: '3.8'

services:
  triad:
    image: lsbnb/triad:latest
    container_name: triad_app
    ports:
      - "5001:5001"
    volumes:
      - /dev/shm:/dev/shm
      - ./netMHCpan-4.2:/opt/netMHCpan-4.2
    restart: unless-stopped

Run with:

docker compose up -d

⁠📊 Output Data Format & Column Ordering

Output tables and exported CSV / Excel reports strictly follow standard NetMHCpan ordering with Protein ID / Identifier positioned in the first column:

⁠🌐 REST API Usage Examples

⁠1. Check System Specs & RAM Disk Status

curl -s http://localhost:5001/api/system_resources | jq .

⁠2. Submit Prediction Payload

curl -s -X POST http://localhost:5001/api/predict \
  -H "Content-Type: application/json" \
  -d '{
    "mode": "peptide",
    "input": "AAAWYLWEV\nAEFGPWQTV\nYLLPAIVHI\nGILGFVFTL",
    "alleles": ["HLA-A*02:01", "HLA-B*07:02"],
    "include_ba": true
  }'

⁠3. Download Filtered CSV Report

curl -O http://localhost:5001/api/download/<JOB_ID>/csv

⁠🔬 Literature & References

1. NetMHCpan Presentation Model:
   Reynisson B, et al. NetMHCpan-4.1 and NetMHCIIpan-4.0: improved predictions of MHC antigen presentation. Nucleic Acids Res. 2020;48(W1):W449-W454. doi:10.1093/nar/gkaa379⁠
2. T-Cell Immunogenicity Model:
   Calis JJ, et al. Properties of MHC Class I Presented Peptides That Inspire Immunogenicity. PLoS Comput Biol. 2013;9(10):e1003266. doi:10.1371/journal.pcbi.1003266⁠
3. Population Coverage Database:
   Gonzalez-Galarza FF, et al. Allele frequency net database (AFND) 2020 update. Nucleic Acids Res. 2020;48(D1):D783-D788. doi:10.1093/nar/gkz1029⁠

⁠🏛️ Maintained By

Laboratory of Systems Biology and Bioinformatics (LSBNB)
Institute of Information Science, Academia Sinica, Taipei, TAIWAN.
Web: https://hub.docker.com/r/lsbnb/triad⁠