Quick start
This walkthrough covers an oncology study from creation through mutation landscape analysis and optional AI interpretation.
1. Create a study
Click Create study from the oncology dashboard. Enter a name (for example IO cohort demo) and optional tumor type, cancer stage, treatment arm, or response status metadata.
2. Add samples and clinical data
Open the study Data page. Register samples with patient/sample identifiers, timepoints, and group labels. Add clinical endpoints (survival time, event status, treatment arm) when available.
3. Upload a mutation file
The mutation landscape pipeline accepts a MAF-style CSV with columns like Hugo_Symbol, Tumor_Sample_Barcode, Variant_Classification, Chromosome, Start_Position, Reference_Allele, and Tumor_Seq_Allele2. No file handy? See Sample data for a minimal example you can save and upload.
4. Run mutation landscape
On the Mutations page, select your uploaded MAF file, set the panel size and number of top genes to highlight, and click Run mutation landscape. Track progress in the Jobs panel.
Review TMB per sample, gene frequency table, oncoprint matrix, and mutational signature summary once the run completes.
5. Run survival analysis (optional)
Upload a clinical CSV with patient_id, time_to_event_days, and event_observed columns, then on the Survival page select it and set a stratification field (e.g. treatment arm).
6. Interpret (optional)
After one or more pipeline runs complete, open Interpret and select the completed runs you want summarized.
If Interpret isn't available in your workspace, ask your administrator to enable AI interpretation.
Next steps
- Key concepts
- Data upload — samples, clinical endpoints, MAF, and repertoire formats
- Pipelines reference — all available analysis steps