Multiplex IF phenotyping
Turn a multi-channel immunofluorescence image and a completed cell segmentation into per-cell marker positivity, phenotype calls, and region-level composition — beyond what H&E morphology alone can resolve.
Research question
Which marker-positive cell populations are present in this tissue, how do markers co-occur on the same cells, and how does phenotype composition vary across tissue regions?
Who this is for
- Translational and tumor biology researchers mapping immune or tumor marker panels across tissue
- Immuno-oncology labs quantifying checkpoint marker-positive populations (e.g. PD-L1+ tumor or stroma)
- Pharma tissue biomarker teams building marker-panel-based histological endpoints
Data requirements
| Data | Required | Purpose |
|---|---|---|
| Multi-channel OME-TIFF (multiplex IF) | Yes | Per-channel marker intensity source |
| Completed Segment cells run for the slide | Yes | Cell objects that marker intensity is sampled against |
| Marker panel configuration (channel → marker name) | Recommended | Drives phenotype rule matching; falls back to detected channel names |
Workflow
Upload multiplex IF slide → Tiles → Segment cells
→ Multiplex IF phenotyping (marker thresholds + panel)
→ Review phenotype overlay, co-expression, and region composition
Step 1 — Prepare channels and segmentation
Upload the multi-channel OME-TIFF, generate tiles, and run Segment cells so per-cell objects exist for marker sampling. Review per-channel thumbnails and intensity histograms to judge reasonable positivity thresholds before running the pipeline.
Step 2 — Run Multiplex IF phenotyping
On the slide detail page, run Multiplex IF phenotyping against the completed segmentation. Configure the marker panel (channel-to-marker mapping) and per-channel positivity thresholds using the histogram preview; background/autofluorescence correction is applied per channel when enabled.
The pipeline samples marker intensity per cell from its segmented bounding box/centroid, thresholds each channel for positivity, and applies phenotype rules — for example CD8+ T cell, CD68+ macrophage, PD-L1+ tumor/stroma — plus a generic marker-combination fallback for panels without a named rule.
Step 3 — Review phenotypes
Toggle the phenotype map overlay in the slide viewer to see phenotype-colored cells on the WSI. Review the co-expression matrix (how often marker pairs are positive on the same cell) and the region composition table when tissue regions or annotations exist.
Expected outputs
- Per-cell phenotype table (
phenotypes.parquet) with marker positivity and assigned phenotype - Marker summary (
marker_summary.json) with per-channel positivity rates - Region composition (
composition_by_region.json) — phenotype frequency by tissue region - Phenotype-map overlay for the slide viewer
Typical analyses
| Analysis | Question |
|---|---|
| Checkpoint marker mapping | What fraction of tumor cells are PD-L1+? |
| T-cell subset mapping | Where are CD8+ T cells concentrated relative to tumor regions? |
| Marker co-expression | Do CD68 and PD-L1 co-occur on the same myeloid cells? |
| Panel-wide phenotyping | How does phenotype composition differ between annotated tumor and stroma regions? |
Important caveats
Phenotype calls depend on threshold choices, background correction, and segmentation quality — review the marker histograms and overlay visually before treating a phenotype fraction as a stable measurement. This is a research tool, not a validated clinical multiplex assay pipeline.