Malignant cell detection
Malignant cell detection turns Computational Biology single-cell CNV output into oncology-facing tumor biology summaries. It does not recompute copy-number signal. Instead, it consumes the CompBio single_cell_cnv handoff or result JSON and organizes malignant labels, CNV events, subclones, mutation overlap, and response features for oncology workflows.
Prerequisites
- A completed CompBio
single_cell_cnvrun withoncology_handoff.jsonor equivalent result JSON - Optional mutation landscape result JSON for gene overlap with inferred CNV events
- Optional communication or survival result JSON for downstream context
Launching the pipeline
Open the study Analyze page and use Malignant cell detection, selecting the completed CompBio CNV run (and optionally a mutation landscape run) to pull context from.
Key parameters
| Parameter | Required | Purpose |
|---|---|---|
cnv_result_path | Yes | CompBio single-cell CNV handoff or result JSON |
mutation_result_path | No | Completed mutation landscape result JSON for inferred event-gene overlap |
communication_result_path | No | Completed communication result JSON for context-aware handoff notes |
survival_result_path | No | Completed survival result JSON for outcome context |
Outputs
| Output | Description |
|---|---|
summary | Source run, malignant fraction, subclone count, event count, and linked-context flags |
malignant_populations | Groups called likely malignant with fraction, burden, confidence, reason, and top CNV evidence |
subclone_tme_features | CNV subclone rows prepared for communication sender grouping |
cnv_events | Inferred top events carried over from the CompBio result |
mutation_overlap | Overlap between inferred event genes and supplied mutation/CNA result genes |
survival_response_features | Feature rows for malignant fraction, CNV burden, subclone fractions, and key inferred events |
workflow_handoffs | Suggested metadata columns and groupings for communication, mutation, survival, and immune workflows |
caveats | Research-use warnings from the CompBio run plus oncology interpretation caveats |
The frontend result panel shows malignant populations, top CNV evidence, subclone TME handoff rows, mutation overlap, downstream feature counts, and copy buttons for summary, survival-feature, and malignant-population artifact paths.
Typical use cases
- Review malignant clusters as tumor biology before running TME communication.
- Stratify communication by malignant subclone sender and immune/stromal receiver.
- Compare inferred CNV-event genes with mutation/CNA outputs.
- Export malignant fraction, CNV burden, and subclone fractions as response or survival features.
- Ground multi-run interpretation in CNV, immune, mutation, and outcome evidence.
Caveats
This analysis is research-only. It depends on the quality of the CompBio CNV run, especially gene order and reference-cell selection. Use DNA copy-number, mutation, histology, or orthogonal annotations where available for confirmation.