Figure 2.
Figure 2. Presence of candidate driver (CD) mutations by age. (A) VAF vs age at blood draw for the 16 CD genes where mutations were detected. The 177 subjects who were classified as WGS-outliers are plotted as blue points, and the 69 subjects who were not outliers are plotted as red points. (B) Conditional probability of being identified as a WGS-outlier given that a CD mutation was detected, stratified by age bins. P = 1.9 × 10−12; β = 0.10, assessed by logistic regression. Error bars indicate 95% confidence intervals. (C) Co-mutation plot for WGS-outliers and nonoutliers in whom CD mutations were detected. Each column represents a subject, each row a candidate pre-leukemic driver gene. Cells are shaded if a mutation was detected, and the color of the shading indicates the number of mutations detected for the particular gene. The vertical black line separates non–WGS-outlier from WGS-outlier subjects.

Presence of candidate driver (CD) mutations by age. (A) VAF vs age at blood draw for the 16 CD genes where mutations were detected. The 177 subjects who were classified as WGS-outliers are plotted as blue points, and the 69 subjects who were not outliers are plotted as red points. (B) Conditional probability of being identified as a WGS-outlier given that a CD mutation was detected, stratified by age bins. P = 1.9 × 10−12; β = 0.10, assessed by logistic regression. Error bars indicate 95% confidence intervals. (C) Co-mutation plot for WGS-outliers and nonoutliers in whom CD mutations were detected. Each column represents a subject, each row a candidate pre-leukemic driver gene. Cells are shaded if a mutation was detected, and the color of the shading indicates the number of mutations detected for the particular gene. The vertical black line separates non–WGS-outlier from WGS-outlier subjects.

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