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Table 5 Stepwise context reduction for the Ancestral Repeats 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)

[623.2; 638.2]

[645.5; 661.9]

642.2

GTR15C

15 (90)

[658.0; 672.1]

[665.0; 682.0]

669.2

GTR14C

14 (84)

[651.9; 668.4]

[664.3; 678.9]

665.9

GTR13C

13 (78)

[661.7; 675.9]

[672.6; 686.4]

674.2

GTR12C

12 (72)

[679.8; 694.7]

[695.8; 714.7]

696.3

GTR11C

11 (66)

[676.5; 692.7]

[694.4; 709.7]

693.3

GTR10C

10 (60)

[686.0; 700.1]

[698.9; 715.5]

700.1

GTR9C

9 (54)

[675.3; 689.0]

[685.5; 701.1]

687.7

GTR8C

8 (48)

[656.7; 669.7]

[678.5; 695.6]

675.1

GTR

1 (6)

-

-

0

  1. The stepwise context reduction for the Ancestral Repeats dataset using the likelihood-based clustering approach reveals an optimal model with 10 clusters (GTR10C). It attains a log Bayes Factor of 700.1 (over GTR1C), which is a significant improvement over the full context-dependent model (GTR16C) that has 36 additional parameters. Further reducing the number of contexts decreases model fit.