Welcome to PharmGEO

PharmGEO is a comprehensive, manually curated, and quality-controlled platform that systematically integrates pharmaco-transcriptomic data from the GEO database.

7,931

Pharmaco-transcriptomics Datasets

1,334

Unique Drugs with Metadata

17,776

Average Genes per Dataset

115,264

Drug-Drug Interactions

RNA-seq Datasets

  • Access 7,931 curated datasets
  • Standardized metadata annotations
  • Differential expression analysis
  • Pathway enrichment results

Drug Information

  • 1,334 drugs with detailed profiles
  • High-consistency gene signatures
  • GMCS quality metrics
  • PubChem integration
  • Literature evidence support

Gene Information

  • Gene-centric drug associations
  • Cross-dataset validation
  • GeneCards integration

Drug-Drug Interactions

  • 119,298 interaction records
  • Transcriptomic-level evidence
  • Multi-source integration
  • Network visualization

Introduction

This section presents a curated collection of pharmacotranscriptomic datasets systematically retrieved from the GEO database. You can efficiently browse and select datasets for in-depth analysis, including metadata inspection, differential gene expression profiling, and advanced functional enrichment analyses such as GO, KEGG, and GSEA.

Dataset Selection

Please select a dataset from the table below, then click Analyze to proceed.

Introduction

The Drug Information section provides details on specific drugs, including molecular properties, descriptions, and related genes. It also lists genes consistently found across datasets to identify key gene-drug interactions.

Drug Information

Highly Consistent Genes

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Introduction

The Drug-Drug Interaction section analyzes interactions between drugs. Selecting two drugs displays their details, intersecting genes, and interaction data from multiple databases(DDInter, MecDDI, RxNav). A network visualization further illustrates the drug-gene interaction relationships.

Select a Gene:
Hot Genes:
All Genes:

Gene Information

Associated Drugs

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Introduction

The Drug-Drug Interaction section enables users to explore and analyze interactions between different pharmaceutical compounds. Users can select two drugs to view their detailed information, intersecting genes, and interaction details from multiple databases. Additionally, an interaction network visualization provides insights into the relationships between the selected drugs and associated genes.

Select Drugs

Drug Information

Available Downloads

Annotated Drug Metadata

Download curated drug annotation metadata (Excel format).

Differential Gene Lists

Download experiment-specific lists of significantly differentially expressed genes (Rdata format).

PharmaGEO Help Guide

Module 1: RNA-seq Datasets

Purpose

The RNA-seq Datasets module provides access to drug-related bulk RNA-seq and microarray transcriptomic datasets systematically curated from the GEO database. This section serves as the primary entry point for dataset-specific analyses of pharmaco-transcriptomic studies.

RNA-seq Datasets Interface

Key Functionalities

1. Dataset Selection and Exploration

  • Interactive Table: Browse through 7,780 curated pharmaco-transcriptomic datasets
  • Metadata Filtering: Filter datasets by drug name, organism, cell type, dose, duration, and experimental conditions
  • GEO Integration: Direct links to original GEO accession numbers (GSE) for data provenance
  • Comprehensive Metadata: View dataset-specific information including drug name, dose, duration, cell type, organism, and platform details

Dataset Selection

2. Metadata Analysis

  • Standardized Annotations: Each dataset includes the following metadata fields:
    • standard_name: Standardized drug name using PubChem database nomenclature
    • drug_name: Original drug name as recorded in the GEO database
    • organism: Species of the sequenced samples
    • cell_type: Cell line or tissue type used in the sequencing experiment
    • dose: Drug dosage concentration administered
    • duration: Duration of drug treatment
    • gse_id: Unique identifier for each dataset in the GEO database (clickable link to GEO page)
    • GPL: Sequencing platform identifier providing technical parameter information
    • ctrl_ids: Sample identifiers used as control group in differential expression analysis
    • pert_ids: Sample identifiers used as treatment group in differential expression analysis
    • type: Perturbation type - PharmGEO database exclusively contains drug-type perturbations
    • Exp_type: Experimental platform type: includes 4,438 microarray datasets (Expression profiling by array) and 3,342 high-throughput sequencing datasets (Expression profiling by high throughput sequencing)

Dataset Metadata

3. Differential Expression Analysis

  • Volcano Plot Visualization: Interactive plots showing log fold change vs. statistical significance
  • Gene Expression Tables: Comprehensive lists of differentially expressed genes with:
    • genes: Gene symbols with direct links to GeneCards
    • logFC: Log fold change values
    • p.value: Filtered p.value < 0.05

Differential Expression Analysis

4. Enrichment Analysis

Three complementary enrichment analysis approaches with interactive dot plot visualizations:

Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway Analysis
  • Interactive dot plots showing enriched pathways
  • X-axis: Gene count, Y-axis: Pathway descriptions
  • Color coding by statistical significance (p-value)
  • Point size representing gene count
Gene Ontology (GO) Analysis
  • Interactive dot plots for biological processes, molecular functions, and cellular components
  • X-axis: Gene count, Y-axis: GO term descriptions
  • Color coding by statistical significance (p-value)
  • Point size representing gene count
Gene Set Enrichment Analysis (GSEA)
  • Interactive dot plots showing gene set enrichment
  • X-axis: Normalized enrichment score (RichFactor), Y-axis: Gene set descriptions
  • Color coding by statistical significance (p-value)
  • Point size representing gene count

Enrichment Analysis

Module 2: Drug Information

Purpose

The Drug Information module enables detailed exploration of individual drugs and their associated gene signatures. This section focuses on drug-centric analysis with emphasis on consistency and variability metrics.

Drug Information Interface

Key Functionalities

1. Drug Selection and Properties

  • Comprehensive Drug Database: Access to 1,311 unique drugs.

Drug Selection

  • Molecular Information: Detailed drug properties including:
    • Chemical Structure Visualization: 2D molecular structure display
    • Drug Name: Standardized drug name
    • CID: Canonical chemical identifier
    • Formula: Molecular formula
    • Weight: Molecular weight in g/mol
    • Description: Comprehensive pharmacological description.
    • IUPAC Name: International Union of Pure and Applied Chemistry nomenclature
    • InChI: International Chemical Identifier string
    • InChIKey: Standardized InChI key for database searching
    • SMILES: Simplified Molecular Input Line Entry System representation

Drug Information

2. Highly Consistent Gene Analysis

Gene Mean Consistency Score (GMCS)
  • Formula: GMCS = (∑ᵢ₌₁ⁿ countᵢ) / n
  • Purpose: Measures gene expression consistency across datasets
  • Interpretation: Higher values indicate more consistent drug-gene associations

3. Gene Association Tables

  • High-Confidence Genes: Filtered for Top 25% consistency and Bottom 25% variability
  • Literature Support: PubMed co-occurrence counts for drug-gene pairs
  • ATC Classification: Anatomical Therapeutic Chemical classification system integration
  • Cross-References: Direct links to external databases (GeneCards, PubChem, WHO-ATC)

Gene Association

Module 3: Gene Information

Purpose

The Gene Information module provides gene-centric analysis, allowing users to explore which drugs affect specific genes and understand gene-drug relationship patterns.

Gene Information Interface

Key Functionalities

1. Gene Selection Options

  • Hot Genes: Quick access to 20 frequently studied genes (TP53, EGFR, KRAS, etc.)
  • Comprehensive Search: Search through complete gene database with live filtering

Gene Selection

2. Gene Annotation

  • Gene Cards Integration: Comprehensive gene information including:
    • Official gene names and symbols
    • Chromosomal location
    • Entrez and MIM identifiers
    • Gene aliases and alternative names
    • Quick link to GeneCards

Gene Annotation

3. Drug Association Analysis

  • Associated Drugs Table: Comprehensive list of drugs affecting the selected gene
  • Quality Metrics: GMCS values for each drug-gene pair
  • Therapeutic Classification: ATC Level 3 codes and descriptions
  • Literature Evidence: PubMed co-occurrence statistics

Drug Association

Module 4: Drug-Drug Interaction

Purpose

The Drug-Drug Interaction module represents the first systematic transcriptomic-level analysis of drug interactions, providing mechanistic insights through shared gene targets.

Drug-Drug Interaction Interface

Key Functionalities

1. Drug Pair Selection

  • Interactive Selection: Choose two drugs from the comprehensive database
  • Validation: Automatic filtering for available interaction data
  • Real-time Updates: Dynamic drug B options based on drug A selection

DDI Selection

2. Molecular Information Display

  • Dual Drug Profiles: Side-by-side comparison of drug properties
  • Chemical Structures: Visual representation of molecular structures
  • Pharmacological Properties: Detailed molecular and pharmacokinetic information

Drugs Information

3. Gene Intersection Analysis

  • Shared Target Identification: Genes affected by both drugs
  • Directional Analysis: Expression change patterns for each drug
  • Interaction Categories (where A = Drug A, B = Drug B):
    • A_up_B_down: Gene upregulated by Drug A but downregulated by Drug B
    • A_down_B_up: Gene downregulated by Drug A but upregulated by Drug B
    • A_up_B_up: Gene upregulated by both Drug A and Drug B
    • A_down_B_down: Gene downregulated by both Drug A and Drug B

DDI Intersecting Genes

4. Multi-Source DDI Evidence

Integration of three major drug interaction databases:

  • DDInter: Comprehensive drug-drug interaction database
  • MecDDI: Mechanism-based drug-drug interactions
  • RxNav: Clinical drug interaction information

Multi-Source Support

5. Network Visualization

  • Interactive Network Graph: ECharts-based visualization showing:
    • Drug nodes (distinct colors)
    • Gene nodes (categorized by interaction type)
    • Connection patterns between drugs and genes
  • Customizable Display: Adjustable top N genes per category
  • Dynamic Updates: Real-time network modification

DDI-Genes Network