Welcome to PHELEX!
PHELEX (Pulmonary Hypertension Engine for Linked Experiments) is a community research platform designed to help investigators explore, filter, and make use of publicly available data for biomarker discovery, validation, and hypothesis development. The application is integrated with CONFIDENCE Software, which applies four complementary differential gene expression analyses to raw counts, supporting reliable gene prioritization.
The NCBI’S Gene Expression Omnibus database(GEO) hosts millions of gene expression experiments spanning human, mouse, rat, and other model organisms. Leveraging and reanalyzing data across multiple independent studies enhances statistical power, enabling the identification of new and more reliable biological insights compared to analyzing single datasets in isolation. Such secondary analyses can also guide experimental design. However, this process often requires detailed study information, as well as computational and statistical expertise, which may limit direct use by many biologists.
With PHELEX, users can:
- Search GEO datasets using keywords, with options to filter by species, tissue source, and dataset type.
- Compare datasets and conduct exploratory meta-analyses across studies.
- Combine data from multiple studies to generate a gene-by-sample counts matrix.
- Analyze counts matrix data using the integrated CONFIDENCE Software.
Currently, PHELEX supports bulk-RNA sequencing (NGS) datasets related to pulmonary hypertension, with future updates planned to expand support to additional datasets. For questions or feedback, please email at Dr. Hindmarch at c.hindmarch@queensu.ca
Copyright © 2026 Charles Colin Thomas Hindmarch. All rights reserved. The PHELEX and CONFIDENCE application, including but not limited to its source code, object code, algorithms, architecture, design, documentation, user interface, and all related materials (collectively, the “Software”), is the sole and exclusive intellectual property of Dr Charles Colin Thomas Hindmarch. All rights, title, and interest in and to the Software are owned exclusively by Dr Hindmarch. No rights are granted except as expressly provided in a written license agreement. Unauthorized reproduction, modification, distribution, reverse engineering, or use of the Software is strictly prohibited.
Workflow
Search for a Dataset
- Enter keyword or GEO ID
- Filter by species/tissue
- Select dataset
Select Samples & View Metadata
- Filter samples
- View protocols
- Subset samples of interest
- Check annotations
Assign Condition Labels
- Label controls and treatments
- Review labels
- Build count matrix
Run Differential Gene Expression
- Select methods
- Set p-value threshold
- View PCA & volcano plots
- Filter by Confidence Score
Compare Across Datasets
- Save results to workspace
- View common DEGs
- View forest plots
- Run pathway enrichment on shared genes
Summary of pulmonary hypertension RNA-Seq datasets available on PHELEX
Total Datasets
Total Samples
Species
📅 Last updated: March 2026
Search & Filters
Build Metadata Table
Selected GEO IDs
1. Curate Selected Columns
Select columns from the table, then rename them below:
2. Assign Conditions
Click below to show/hide the condition assignment panel.
Download Curated CSV Download Raw Metadata (CSV)
Raw Metadata Table
Filter Rows by Value (Optional)
Condition Assignment Panel
Define Groups
Condition 1
Condition 2
Select rows and assign to conditions
Use the table below to select rows (click or use checkboxes), then click an 'Assign' button on the left.
Curated Preview (IDS + your cleaned columns + conditions if assigned)
Current Mapping
Build Counts Matrix
Confidence Analysis
Welcome to Confidence. Follow the steps below to import your metadata and gene counts for analysis.
Step 1: Upload Experimental Metadata
Upload a CSV file containing your sample information and experimental conditions.
Example Metadata
| Sample | Diet | Sex |
|---|---|---|
| Sample 1 | Control | Male |
| Sample 2 | High Fat | Female |
| Sample 3 | High Fat | Male |
Option 1: Import Metadata from PHELEX
Option 2: Upload Metadata File (CSV)
Results will show up here after you import and run your data through CONFIDENCE!
Multi-Dataset Comparison
Select analyses from your workspace to discover overlapping significant genes.
1. Select Datasets
2. Parameters
⚠️ Showing genes significant in all selected datasets at the selected threshold.
UpSet Plot
DownloadGene Overlap Table
Select rows to display them in the Forest Plot below.
Forest Plot
DESeq2 log₂ fold change with 95% CI for the genes you've selected above.
Pathway Enrichment Analysis
Identify biological pathways over-represented in the intersection gene set.
Workspace
Manage your saved datasets, view results, or quickly re-start an analysis.
Getting Started
Follow these 14 steps to go from a GEO search to a multi-dataset meta-analysis.
Go to the Select Data tab and enter keywords or a GEO accession number to find datasets.
In the search results table, click the Clean Metadata button next to the dataset you want. You will be taken to the Clean Metadata tab with that study pre-loaded.
Three sub-steps:
- Select columns from the raw metadata table (e.g. characteristics, tissue, condition).
- Filter rows based on the values in those columns to keep only relevant samples.
- Assign custom conditions if needed <e2><80><94> map existing labels to clean group names (e.g. "Idiopathic PAH" <e2><86><92> "PH", "Healthy Donor" <e2><86><92> "Control").
Navigate to the Counts tab. PHELEX assembles a gene expression counts matrix for the curated samples. If pre-processed counts are available, this happens automatically.
Switch to the Confidence tab and click Import Data to load the curated metadata you built in Step 3.
- Factor <e2><80><94> for discrete groups (e.g. PH vs. Control).
- Continuous <e2><80><94> for a numeric covariate (e.g. age, pressure).
Choose the species your samples come from (e.g. Human, Mouse, Rat).
Enter the number of samples in the smallest experimental group (e.g. if you have 5 PH and 8 controls, enter 5 ).
Click Import Counts to load the counts matrix from Step 4. PHELEX matches sample IDs between the metadata and counts matrix automatically.
- Reference = the baseline group (e.g. Control).
- Comparison = the experimental group (e.g. PH).
After the analysis runs, click Save to Workspace in the Confidence module to store the DGE results for later comparison.
Go back to Step 1 for each additional dataset:
- Search <e2><86><92> Clean Metadata <e2><86><92> Build Counts
- Import into Confidence <e2><86><92> Configure <e2><86><92> Run
- Save to Workspace <e2><86><92> Reset
Navigate to the Compare Data tab to explore meta-analysis results:
- Common differentially expressed genes across studies
- Forest plots of effect sizes
- Venn diagrams of gene overlaps
- Pathway enrichment on shared gene lists