TABLE 3

Results of codon-based models for detecting selection for variable domain

ModellaϖbParametersc
M0 (single ω)−1553.470.803ω = 0.803
M1 (neutral)−1549.380.737ω0 = 0 (p0 = 0.26)
ω1 = 1 (p1 = 0.74)
M2 (selection)−1549.010.948ω0 = 0 (p0 = 0.28)
ω1 = 1 (p1 = 0.39)
ω2 = 1.40 (p2 = 0.33)
M3 (discrete)−1548.910.852ω0 = 0 (p0 = 0.42)
ω1 = 1.36 (p1 = 0.37)
ω2 = 1.36 (p2 = 0.21)
M7 (β)−1549.470.710α = 0.04; β = 0.014
M8 (β + ω)−1549.020.844p0 = 0.30; α = 0.001;
   β = 1.83
p1 = 0.70; ω = 1.20
  • a Log-likelihood of data.

  • b Mean dN/dS ratio for entire domain.

  • c pi, the proportion of codons that falls in each category.