Study workflow
Oncology follows a left-to-right research flow connecting molecular data to clinical outcomes. Sample and clinical metadata should be registered before launching analysis pipelines.
Create study → Register samples & endpoints → Upload mutation/repertoire data → Run oncology pipelines → Interpret → Report
Dashboard — area home
The oncology dashboard (/areas/oncology/dashboard) shows recent studies and links to create a new study.
Readiness signal: at least one study with registered samples and one completed analysis run.
Study overview — project hub
The study page (/areas/oncology/studies/{id}) is your project hub:
- Study metadata — tumor type, stage, treatment arm, response status
- Workflow cards — links to TME, communication, immune, mutations, survival, and interpret pages
- Run history — all pipeline runs for this study
Data — cohort organization
The data page (/areas/oncology/studies/{id}/data) manages:
- Sample records with patient/sample keys and timepoints
- Clinical endpoint records for survival and response
- Mutation and repertoire dataset registrations
See Data upload.
Analysis workflow pages
Each analysis type has a dedicated page under the study:
| Page | Route | Purpose |
|---|---|---|
| TME | /tme | Tumor microenvironment composition (compbio-backed) |
| Communication | /communication | Ligand-receptor and signaling network analysis |
| Immune | /immune | Immuno-oncology profiling and repertoire metrics |
| Mutations | /mutations | Somatic mutation landscape and oncoprint |
| Survival | /survival | Kaplan-Meier, log-rank, and Cox regression |
| Interpret | /interpret | AI-assisted summaries of completed runs |
See the Analysis guides section for pipeline details on each page.
Typical paths
| Study type | Path |
|---|---|
| Mutation-first cohort | Register samples → upload MAF → mutation landscape → survival stratified by TMB |
| IO responder analysis | Register samples with response labels → immune profile → cell communication with condition comparison → interpret |
| Multi-omic integration | TME (compbio) → communication → immune profile → mutation landscape → survival → interpret |
| Translational endpoint | Clinical endpoints → survival with molecular feature stratification → interpret |
Integration with other areas
- Computational Biology — single-cell TME profiling, spatial transcriptomics, differential expression, biomarker ML
- Pathology — whole-slide imaging for pathology-integrated spatial TME context
Oncology consumes these capabilities rather than duplicating them. See products/oncology/product.md for the full integration map.