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Table 8 Stepwise context reduction for the nuclear SSU rRNA dataset using the likelihood-based approach.

From: Efficient context-dependent model building based on clustering posterior distributions for non-coding sequences

Model Contexts Annealing Melting log BF
GTR16C 16 (96) [-21.25; -15.74] [-19.29; -14.31] -17.65
GTR15C 15 (90) [-17.17; -13.45] [-14.19; -10.30] -13.78
GTR14C 14 (84) [-14.05; -10.21] [-10.09; -5.13] -9.87
GTR13C 13 (78) [-11.07; -7.85] [-6.80; -3.42] -7.28
GTR12C 12 (72) [-2.61; 1.25] [-0.71; 3.31] 0.31
GTR11C 11 (66) [-0.11; 3.55] [0.62; 3.77] 1.96
GTR10C 10 (60) [-2.33; 1.28] [8.76; 13.06] 5.19
GTR9C 9 (54) [6.94; 10.27] [9.03; 13.94] 10.05
GTR8C 8 (48) [9.54; 12.82] [12.12; 16.21] 12.67
GTR7C 7 (42) [12.80; 16.45] [18.26; 22.96] 17.62
GTR6C 6 (36) [13.75; 16.89] [21.71; 26.13] 19.62
GTR5C 5 (30) [15.87; 18.89] [17.86; 22.19] 18.70
GTR4C 4 (24) [13.03; 16.88] [17.38; 20.71] 17.00
GTR3C 3 (18) [9.43; 12.63] [12.61; 15.66] 12.58
GTR2C 2 (12) [11.69; 15.19] [12.84; 16.58] 14.08
GTR 1 (6) - - 0
  1. The stepwise context reduction using the likelihood-based clustering approach reveals an optimal model with six clusters for the nuclear SSU rRNA dataset (GTR6C). It attains a log Bayes Factor of 19.62 (as compared to GTR1C), a significant improvement over the full context-dependent model (GTR16C).