DROMA Components

Overview

DROMA_DB is the foundational component that converts diverse omics datasets into a structured SQLite database. It provides efficient data storage and retrieval for multi-omics drug response studies across different model systems.

Key Features

• Unified database structure for heterogeneous data
• Project-oriented architecture with 18+ datasets
• Optimized SQLite with indexing for fast queries
• Comprehensive metadata management
• Support for multiple model systems (Cell Lines, PDOs, PDXs, PDCs)

Database Content

Contains comprehensive data from 18 projects including:

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

Overview

DROMA_Set is a comprehensive R package that provides robust S4 classes for managing and analyzing drug response and omics data across multiple projects. It enables seamless cross-project comparisons and analyses.

Core Classes

Key Features

• Flexible data loading with filtering options
• Sample overlap detection across projects
• Comprehensive metadata management
• Database connectivity and efficient querying
• Support for all molecular profile types

# Install from GitHub
devtools::install_github(
  "mugpeng/DROMA_Set"
)

# Create DromaSet
gCSI <- createDromaSetFromDatabase(
  "gCSI", "droma.sqlite"
)

# Load data
gCSI <- loadMolecularProfiles(
  gCSI, "mRNA", c("BRCA1", "TP53")
)

Overview

DROMA_R provides advanced statistical analysis and visualization functions for drug-omics associations. It supports meta-analysis across multiple datasets and comprehensive biomarker discovery workflows.

Analysis Methods

Visualization Outputs

• Forest plots for meta-analysis results
• Volcano plots for batch analysis
• Scatter plots for continuous associations
• Box plots for discrete comparisons
• Publication-ready figure themes

Overview

DROMA_MCP is a Model Context Protocol server that bridges AI assistants with cancer pharmacogenomics analysis. It enables natural language interactions with the DROMA ecosystem through ChatGPT, Claude, and other AI assistants.

AI Capabilities

Integration Examples

# Install via pip
pip install droma-mcp

# Start server
droma-mcp run --db-path droma.sqlite

Overview

DROMA_Py provides a Pythonic interface to the DROMA ecosystem, enabling Python data scientists and bioinformaticians to access and analyze cancer pharmacogenomics data seamlessly. It bridges the gap between R-based DROMA components and Python workflows.

Core Capabilities

Python Integration

• Pandas DataFrame integration
• NumPy array support
• Type hints for better IDE support
• Comprehensive error handling
• Jupyter notebook compatibility

# Install from PyPI
pip install droma-py

# Basic usage
import droma_py as dp
db = dp.DROMADatabase("droma.sqlite")

# Load molecular data
data = db.load_molecular_profiles(
    "CCLE", "mRNA", features=["BRCA1"]
)

# Harmonize gene names
harmonized = dp.harmonize_gene_names(data)

Overview

DROMA_Web provides an intuitive, browser-based interface for drug response and omics analysis. Built with Shiny, it offers real-time interactive analysis without requiring programming knowledge.

Web Modules

User-Friendly Features

• No programming knowledge required
• Real-time interactive visualizations
• Dynamic filtering and data exploration
• Export results and figures
• Cross-platform browser compatibility