Comparison of cancer type specificity between CHASM and CanDrA.

<p>Comparison of cancer type specificity between CHASM and CanDrA.</p

Feature optimization for GBM. Plotted are the areas under the curves (AUCs) of the receiver operator characteristics acquired through our incremental feature selection process.

<p>Three sets of AUCs are computed from the 10-fold cross-validation (CV) of the training set GBM.Ex (dotted line) and the independent validation (IV) of 2 test sets, GBM.S1 and GBM.S2 (solid and dashed line). On the x-axis are features that are incrementally selected. The dashed box marks the peaks of the cross-validation AUC, which corresponds to the optimal feature set used for CanDrA.</p

Feature optimization for OVC. Plotted are the areas under the curves (AUCs) of the receiver operator characteristics acquired through our incremental feature selection process.

<p>Three sets of AUCs are computed from the 10-fold cross-validation (CV) of the training set OVC.Ex (dotted line) and the independent validation (IV) of 2 test sets, OVC.S1 and OVC.S2 (solid and dashed line). On the x-axis are features that are incrementally selected. The dashed box marks the peaks of the cross-validation AUC, which corresponds to the optimal feature set used for CanDrA.</p

Comparisons among 3 tools: CHASM, MutationTastor, and CanDrA.

<p>Comparisons among 3 tools: CHASM, MutationTastor, and CanDrA.</p

Correlation between mutation score and prevalence.

<p>Twelve algorithms (x-axis) were compared using 4 data sets: (a) GBM mutations in <i>TP53</i>, (b) GBM mutations in <i>PTEN</i>, (c) OVC mutations in <i>TP53</i>, and (d) OVC mutations in <i>KRAS</i>.</p

Additional file 6: Figure S2. of Hotspot mutations delineating diverse mutational signatures and biological utilities across cancer types

The significance of overlap (y-axis, calculated using Fisher exact test) between hotspot-mutation-containing-genes and previously known cancer genes at various adjusted p value cutoffs (x-axis). (PDF 37 kb

Additional file 12: Table S6. of Hotspot mutations delineating diverse mutational signatures and biological utilities across cancer types

Hotspot mutations exclusively detected in only one tumor type in TCGA pan-cancer data. (PDF 70 kb

Additional file 2: Table S2. of Hotspot mutations delineating diverse mutational signatures and biological utilities across cancer types

Twenty mutation subtypes that were included in the statistical modeling of hotspot mutation definition. (PDF 34 kb

Additional file 7: Figure S3. of Hotspot mutations delineating diverse mutational signatures and biological utilities across cancer types

Number of hotspot mutations identified in individual tumor types using COSMIC data. (PDF 183 kb

Additional file 4: Table S4. of Hotspot mutations delineating diverse mutational signatures and biological utilities across cancer types

2 × 2 table of calculating the prevalence of target mutation B in samples A. (PDF 46 kb