Precision Oncology Platform

DROMA
Drug Response Omics association MAp

Bridging cancer pharmacogenomics data and actionable insights through advanced analytics, AI-powered tools, and user-friendly interfaces. The world's largest open-source integrated drug sensitivity dataset with 18 projects, 2,600+ samples, and 56,000+ drugs.

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18 Projects
2,600+ Samples
56K+ Drugs

Key Highlights

Empowering precision medicine through comprehensive data integration

Massive Dataset

World's largest open-source integrated drug sensitivity dataset with comprehensive coverage

Multi-Omics Support

mRNA, CNV, mutations, methylation, proteomics, and more data types

Diverse Model Systems

Cell lines, PDOs, PDXs, and PDCs for comprehensive analysis

AI-Powered

Natural language interactions via MCP server integration

Advanced Analytics

Meta-analysis, biomarker discovery, and statistical modeling

Web Interface

Interactive Shiny application for intuitive browser-based analysis

DROMA Ecosystem

Interconnected components working together seamlessly

Data Infrastructure

DROMA_DB

Database

SQLite database creation and management foundation

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DROMA_Set

Data Management

R package for multi-project data management

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Analysis Engine

DROMA_R

Analytics

Statistical analysis and visualization for drug-omics associations

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DROMA_Py

Python

Python package for database operations and data access

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User Interfaces

DROMA_Web

Web App

Interactive Shiny web interface

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DROMA_MCP

AI Interface

Natural language interactions with AI assistants

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Get Started in Minutes

Begin your drug-omics analysis journey with DROMA's comprehensive ecosystem

1

Install Components

Install DROMA.Set and DROMA.R packages from GitHub

2

Download Data

Get the comprehensive dataset from Zenodo

3

Start Analyzing

Create database and begin your analysis

View Documentation
R 
# Install DROMA packages
devtools::install_github("mugpeng/DROMA_Set")
devtools::install_github("mugpeng/DROMA_R")

# Create database
library(DROMA.Set)
createDROMADatabase("droma.sqlite", "data/")

# Start analysis
gCSI <- createDromaSetFromDatabase("gCSI", "droma.sqlite")
result <- analyzeDrugOmicPair(gCSI, "mRNA", "ABCB1", "Paclitaxel")