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Table 2 Site-specific ExpCM are vastly better than GY94 or ExpCM with preferences averaged or randomized across sites

From: Identification of positive selection in genes is greatly improved by using experimentally informed site-specific models

Gene Model ΔAIC Log likelihood # free parameters: values of selection parameters
Gal4 ExpCM 0 –1048 6: β=0.82, ω=0.13
  GY94 M3 129 –1103 15: ω 1=0.01, ω 2=0.11, ω 3=0.49, p 1=0.50, p 2=0.29
  GY94 M0 192 –1139 11: ω=0.06
  averaged ExpCM 196 –1146 6: β=1.07, ω=0.06
  randomized ExpCM 206 –1151 6: β=0.10, ω=0.07
β-lactamase ExpCM 0 –3421 6: β=1.01, ω=1.02
  ExpCM (Firnberg data) 204 –3523 6: β=1.04, ω=0.65
  GY94 M3 564 –3694 15: ω 1=0.07, ω 2=0.55, ω 3=6.24, p 1=0.69, p 2=0.17
  GY94 M0 765 –3798 11: ω=0.34
  averaged ExpCM 766 –3804 6: β=0.77, ω=0.35
  randomized ExpCM 790 –3816 6: β=0.10, ω=0.34
NP ExpCM 0 –8624 6: β=2.43, ω=0.61
  GY94 M3 2175 –9703 15: ω 1=0.00, ω 2=0.16, ω 3=1.31, p 1=0.59, p 2=0.24
  averaged ExpCM 2584 –9916 6: β=0.43, ω=0.11
  randomized ExpCM 2593 –9921 6: β=0.10, ω=0.11
  GY94 M0 2613 –9926 11: ω=0.11
HA ExpCM 0 –7461 6: β=1.61, ω=0.60
  GY94 M3 1782 –8343 15: ω 1=0.02, ω 2=4.26, ω 3=4.94, p 1=0.59, p 2=0.25
  averaged ExpCM 2137 –8530 6: β=0.42, ω=0.23
  randomized ExpCM 2157 –8539 6: β=0.10, ω=0.23
  GY94 M0 2176 –8544 11: ω=0.22