Figure 4.
Discriminating reactive and MPN samples. (A) PCA of the abstract representations of samples from an annotated cohort showing clusters of reactive cases and MPN disease subtypes. The random forest classifier reached an AUC of 0.98 for discriminating reactive and MPN samples (B) and 0.96 for discriminating reactive and ET samples (C). PC, principal component.

Discriminating reactive and MPN samples. (A) PCA of the abstract representations of samples from an annotated cohort showing clusters of reactive cases and MPN disease subtypes. The random forest classifier reached an AUC of 0.98 for discriminating reactive and MPN samples (B) and 0.96 for discriminating reactive and ET samples (C). PC, principal component.

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