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Redefining false discoveries in cancer data analyses

The nature of biological networks still brings challenges related to computational complexity, interpretable results and statistical significance. Recent work proposes a new method that paves the way for addressing these issues when analyzing cancer genomic data.

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Fig. 1: Overview of FDRnet, proposed by Yang and colleagues.


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Correspondence to Francesco Iorio.

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Competing interests

F.I. receives funding from Open Targets, a public–private initiative involving academia and industry and performs consultancy for the joint CRUK–AstraZeneca Functional Genomics Centre. All the other authors declare no competing interests.

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Najgebauer, H., Perron, U. & Iorio, F. Redefining false discoveries in cancer data analyses. Nat Comput Sci 1, 22–23 (2021).

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