Supplementary Figure 4: Most mutation cluster density scores fit the null distribution and lie on the diagonal in a quantile-quantile plot, indicating that simulations accurately capture the significance of mutation densities. | Nature Genetics

Supplementary Figure 4: Most mutation cluster density scores fit the null distribution and lie on the diagonal in a quantile-quantile plot, indicating that simulations accurately capture the significance of mutation densities.

From: Identification of significantly mutated regions across cancer types highlights a rich landscape of functional molecular alterations

Supplementary Figure 4

Quantile-quantile plots of the observed (y axis) and simulated (x axis) density scores (–log10, PDensity). (a–d) Representative examples from bladder cancer (BLCA) (a), breast cancer (BRCA) (b), colorectal cancer (COLR) (c) and diffuse large B cell lymphoma (DLBC) (d) are shown. The solid line represents the threshold for density score (–log10, PDensity) that guarantees FDR ≤ 5% in each cancer type. The dashed line indicates the line corresponding to y = x. (e) Violin plots of density scores in an expanded set of 90 additional colorectal cancer simulations. (f) The distributions of density scores in the original (10×; blue) and expanded (90×; yellow) sets of simulations are highly concordant and yield tightly correlated FDR estimates for the observed density scores (inset, r2 = 0.99985). Dashed lines indicate thresholds of FDR ≤ 5%. (g) 99.2% (128/129) of SMRs thresholded by FDR (≤5%) are shared by the FDR10 × and FDR90 × thresholded sets.

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