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Fig. 1 | BMC Bioinformatics

Fig. 1

From: An equivalence approach to the integrative analysis of feature lists

Fig. 1

Power curve of the equivalence test, as a function of the true squared Euclidean distance. Balanced case of two gene lists of size 200 with 20 genes in common. Equivalence limit at Δ=0.25. The null hypothesis of the equivalence test states that the true squared Euclidean distance, d, is greater than or equal to Δ, that is to say, that both lists are sufficiently dissimilar according to the Δ limit criterion. Thus, rejecting this hypothesis corresponds to declaring equivalence. When the true simulated distance is d<Δ, not rejecting the null hypothesis not declaring equivalence) corresponds to a false negative. When dΔ, declaring equivalence is a false positive

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