Comprehensive assessment of computational algorithms in predicting cancer driver mutations.

Genome Biol · 2020 · PMC7033911 · PMID 32079540

Europe PMC DOI

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closest p · 1.6× alpha

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marginally significantp = 0.08so close (0.05 < p ≤ 0.1)

In terms of group-based comparisons (Additional file 12 ), algorithms that used epigenomic information had significantly lower AUCs than others (Wilcoxon rank sum test, p = 0.02); cancer-specific algorithms showed marginally significant than the other algorithms (Wilcoxon rank sum test, p = 0.08).

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