Reference Guide
← Back to toolHow to Read the Results
A brief guide to the statistical values displayed by the Tumor Likelihood Tool and how to interpret them.
Prior Probability
The baseline frequency of a tumor type in the GENIE dataset, before any mutation or CNA evidence is considered. It reflects how common each cancer type is among sequenced samples.
Lung cancer is more common in GENIE, so it starts with a higher prior.
Posterior Probability
The updated probability of a tumor type after incorporating your mutation and CNA evidence. This is the main result — tumor types are ranked by posterior, shown as the bold percentage on each card.
Thyroid jumped from 1.46% prior to 22.44% posterior because BRAF V600E is strongly enriched there.
posterior ∝ prior × evidence
Fold Enrichment
How many times more (or fewer) an alteration occurs in a tumor type compared to the overall dataset average. A value of 5.7x means the mutation is 5.7 times more frequent in that tumor type than expected.
Values >1 are enriched (green bar). Values <1 are depleted (orange bar) — the mutation occurs less than expected.
Affected Count / Group Total
The raw frequency displayed as affected / total (percentage). Affected is the number of samples with that alteration in the tumor type. Total is the number of panel-covered samples in that tumor type.
Of 7,727 melanoma samples whose panel covers BRAF, 1,531 carry V600E. The denominator only counts samples whose sequencing panel covers the gene (panel-aware analysis).
Log Bayes Factor
The natural logarithm of the Bayes factor — a measure of how strongly one alteration shifts the probability toward (or away from) a tumor type. This is the engine behind the posterior update.
Each evidence term contributes a weighted log BF. The sum of all weighted log BFs plus the log prior gives the final log score.
Evidence Types & Weights
Each alteration you enter generates one or more evidence terms. Different types carry different default weights reflecting their discriminatory power.
Allele-specific mutations are the most informative, so they receive the highest weight. If a specific protein change isn't in the database, the tool falls back to gene-level evidence at a lower weight.
Drill-Down into Subtypes
Each result card represents a broad tumor group (e.g. LUNG). Click on it to expand and see the detailed cancer subtypes within that group (e.g. Lung Adenocarcinoma, Lung Squamous Cell Carcinoma), along with subtype-specific alteration frequencies.
The broad tumor type ranking uses enrichment statistics computed across 23 major groups. When you expand a card, you see the CANCER_TYPE_DETAILED subtypes within that group, ranked by their own posterior probability. This lets you distinguish, for example, whether a lung sample is more likely adenocarcinoma or squamous cell.
Reading a Result Card
Here's how to interpret each piece of information on a tumor-type result card.
- Tumor type name and posterior percentage appear at the top. This is the probability that the sample belongs to this tumor type, given the alterations you entered.
- Prior shows the baseline prevalence. Compare it to the posterior to see how much the evidence shifted the probability. A large jump means strong evidence.
- Frequency bars show each alteration's frequency in that tumor type. Green bars indicate enrichment (>1x), orange bars indicate depletion (<1x). The label shows the fold enrichment and the raw count.
- Click the card to expand detailed subtypes. Each subtype shows its own posterior and per-alteration frequencies, letting you narrow down the specific cancer type.