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

Faster, but restricts the search to the features Seurat already flagged as variable.

Fits a two-component mixture to every feature, in C++, on the cells you selected at Step 2. Typically seconds to a couple of minutes. Every cell is used — no subsampling — so the index is exact.
The bimodal index cannot be computed on this server.

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
Lower threshold = more contours (less selective)
Higher threshold = fewer contours (more selective)

Save Gate


Saved Gates

How to use:
  • 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.
Start Over: