Step 1: Upload Your Data
✓ Object Loaded Successfully
Available Metadata Columns:
Step 2: Configure Data Subset
Subsetting Strategy
Column Selection
Current Subset Summary
Step 3: Load Bimodal Index
What is Bimodal Index?
The Bimodal Index (BI) measures how well a feature separates cells into two distinct populations.
- Higher BI values: Clear bimodal distribution with distinct peaks → Excellent gating candidate
- Lower BI values: Unimodal or uniform distribution → Poor gating candidate
Tip: BI values can exceed 1.0. Focus on features in the top 5-10% (95th-99th percentile) of your dataset for the best discrimination, regardless of their absolute BI values.
Calculate in the app
The C++ fit could not be compiled at startup, which almost always means no C++ compiler is installed. Install one and restart the app: Rtools on Windows, xcode-select --install on macOS, or build-essential on Linux. The R console where the app started shows the exact error.
✓ Bimodal Index Loaded
Suggested Cutoffs (percentiles):
These values represent the BI score at each percentile. Features above these thresholds are in the top 10%, 5%, or 1% respectively.Selected Features for Gating:
These features passed your threshold and will be available for density contour gating in Step 4.Bimodal Index Distribution
This histogram shows the distribution of BI scores across all analyzed features. The vertical lines indicate percentile cutoffs. Features to the right have higher bimodality.All Features Ranked by Bimodal Index
Browse all features and their BI scores. Click column headers to sort. Use the search box to find specific genes of interest.Step 4: Create Gates by Clicking Contours
Gate Controls
Contour Settings
Higher threshold = fewer contours (more selective)
Save Gate
Saved Gates
- Black contour lines show high-density regions for the selected feature
- Click inside any contour boundary to select all cells within that region
- Selected cells will be highlighted in yellow
- Review selection in 'Current Selection' panel below
- Enter a gate name and click 'Save Selected Cells as Gate'
- Use zoom controls to focus on specific regions
Current Selection
Contour Statistics (Zoomed)
Step 5: Gate Statistics and Analysis
Gated Cells Distribution
Gate Details
Overlap Analysis
Step 6: Export and Save Results
Start a New Session
Clears the loaded object, the bimodal index results and all saved gates, and returns to Step 1.