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. 2019 Jul 25;8:e42906. doi: 10.7554/eLife.42906

Appendix 1—table 6. Results and validation of the linear regression models.

NSP2 was considered as the independent variable and the other viral elements as the dependent variable (see Equation (25)). The slope and standard error for each regression model (Column 2 and 3) were computed in accordance with the Equation (26) and (28) respectively. The t-value of the t-Student distribution function with N-1 degrees of freedom are in Column 4 (see Appendix 1 Section – Linear Regression Model– for details). The p-value for each linear regression model are shows in Column five and were measure as was described in (Equation (29)) and (Equation (30)). Finally, the RSE and the R2 summarize the adjustment of the data through the proposed lineal models. As was advised, the RSE (Column 6) is a fit measure of the linear model to the data (see Equation (27)). The ‘% Error’ is the average error in the prediction and it is computed as: 100×RSE/β, while the 100×R2 is the percent of the data variance that it is explained by the model (see Equation (32)).

Model Slope (β) Std.error (σβ^2) t-value p-value RSE % Error R2
NSP5=βNSP5×NSP2 0.8667494 0.017947738 48.29296 2.550154 × 10−50 0.07 8% 0.974
NSP4=βNSP4×NSP2 0.9911517 0.006973701 142.12708 2.271571 × 10−114 0.035 3.5% 0.995
VP2=βVP2×NSP2 1.1243931 0.014817985 75.88030 6.242800 × 10−72 0.04 3.5% 0.987
VP1=βVP1×NSP2 1.1506138 0.019069730 60.33718 2.238867 × 10−48 0.044 3.8% 0.986
VP6=βVP6×NSP2 1.1806335 0.011218918 105.23595 1.087989 × 10−86 0.038 3.2% 0.992
VP4=βVP4×NSP2 1.3887083 0.024319983 57.10153 5.757257 × 10−50 0.07 5% 0.983
VP7-Mon=βVP7-Mon×NSP2 1.9407204 0.040354225 48.09212 1.560719 × 10−52 0.142 7.3% 0.972
VP7-Tri=βVP7-Tri×NSP2 1.9416542 0.054656327 35.52478 5.778910 × 10−33 0.153 7.8% 0.967