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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).