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

Fig 6

Empirical JTK_CYCLE outperforms the other methods in the presence and absence of asymmetric time series.

Simulated data with rhythmic time series without asymmetry (left, A and C) or with evenly distributed asymmetry (right, B and D) were tested with different methods. The cumulative histograms are plotted before (A and B) and after (C and D) Benjamini-Hochberg multiple hypothesis correction across time series. The vertical axis shows the number of time series with a p-value (P) (A and B) or false discovery rate (FDR, the Benjamini-Hochberg adjusted p-value) (C and D) below or equal to a significance threshold, shown on the horizontal axis. Results shown are for the second simulated dataset with 25% noise, but the effects of Benjamini-Hochberg correction are significantly greater at 50% noise (not shown). The method abbreviations are the same as those in Fig. 4. The legends of A and B correspond to C and D, respectively. The rightmost point on the horizontal axis is 0.2.

Fig 6

doi: https://doi.org/10.1371/journal.pcbi.1004094.g006