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Improved Statistical Methods Enable Greater Sensitivity in Rhythm Detection for Genome-Wide Data

Fig 2

Empirical p-values are uniformly distributed for the null model of JTK_CYCLE.

P-values versus their ranks from lowest (most significant) to highest (least significant) for JTK_CYCLE testing phases at 2 h intervals (green line) or phases and asymmetries at 2 h intervals (blue line) with time series consisting of Gaussian noise. Unbiased estimates should follow the black line (see text). (A) “Initial” p-values from JTK_CYCLE with multiple hypothesis testing underestimate the true p-values. (B) The Bonferroni correction results in p-values that are too high (less significant). (C) The Benjamini-Hochberg correction performs better than the Bonferroni correction but still results in p-values that are generally too high. (D) Empirical p-values that we calculate by permutation are close to uniformly distributed, as desired; their correspondence to the null model improves as the number of hypotheses tested increases.

Fig 2

doi: https://doi.org/10.1371/journal.pcbi.1004094.g002