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. 2018 May 8;114(9):2044–2051. doi: 10.1016/j.bpj.2018.04.006

Figure 2.

Figure 2

Algorithm performance for cp detection calculated on the simulation scheme depicted in Fig. S1A. (A) The power of detection is shown as a function of the noise σ for segment lengths N1=N2=10,20,40,80 (from left to right, represented in different tones of gray) and slopes m1=0.2,0.5 and m2=0.5,0.8 ( and , respectively) with same slope increment |m2m1|=0.3. (B) The power of detection is shown as a function of the noise σ for segment slopes m1=0.2 and m2=0.3,0.5,0.8,1.3 (from left to right, represented in different tones of gray) and lengths N1=13,N2=30(), and N1=N2=20() with similar N (N18andN=20, respectively). (C) The powers of detection for several segment lengths and slopes collapse onto each other once expressed in terms of the rescaled variable ξ, defined in Eq. S6. The lines in (A)–(C) correspond to the function given in Eq. S7. (D) Change point localization precision, normalized to the trace length for traces composed by: segments with slopes m1=0.2,m2=0.3 and lengths N1=20,N2=40(); segments with slopes m1=0.2,m2=0.3 and lengths N1=N2=80(); segments with slopes m1=0.2,m2=0.5 and lengths N1=N2=80(); segments with slopes m1 = 0.2, m2=1.1 and lengths N1=N2=80(). The lines correspond to Eq. S3. (E) The error in the determination of the segment slopes normalized to the modulus of slope difference is shown. Symbols have the same meaning as in (D). Empty or filled symbols refer to the two different segments of the simulated trace. The lines correspond to Eq. S5. (F) The false positive identification rate obtained for α=0.05 on traces of constant slope is shown as a function of σ for different parameter sets: m=0.1,N=40(), m=0.1,N=80(), m=0.1,N=150(), and m=1.1,N=150(). Each point in the plot was obtained from 500 simulated traces. Dashed lines correspond to the average values.