LID SPN TRAP

1450269_a_at

Pfkl phosphofructokinase, liver, B-type

AIM Score vs. Gene Expression
Full X range:
Auto X range:
Group Comparisons: Boxplots

CP73

Model Comparison: AIM ~ expression + C(dose) vs AIM ~ C(dose)

F-statistic p-value df difference
4.354 0.050 1.0

Model:
AIM ~ expression + C(dose) + expression:C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.725
Model: OLS Adj. R-squared: 0.681
Method: Least Squares F-statistic: 16.68
Date: Tue, 28 Jan 2025 Prob (F-statistic): 1.49e-05
Time: 18:40:10 Log-Likelihood: -98.269
No. Observations: 23 AIC: 204.5
Df Residuals: 19 BIC: 209.1
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 260.0232 574.275 0.453 0.656 -941.948 1461.994
C(dose)[T.1] 704.2103 688.369 1.023 0.319 -736.562 2144.982
expression -19.8906 55.497 -0.358 0.724 -136.048 96.267
expression:C(dose)[T.1] -62.8557 66.510 -0.945 0.356 -202.064 76.352
Omnibus: 0.460 Durbin-Watson: 1.898
Prob(Omnibus): 0.794 Jarque-Bera (JB): 0.577
Skew: 0.150 Prob(JB): 0.749
Kurtosis: 2.285 Cond. No. 2.56e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.712
Model: OLS Adj. R-squared: 0.683
Method: Least Squares F-statistic: 24.70
Date: Tue, 28 Jan 2025 Prob (F-statistic): 3.95e-06
Time: 18:40:10 Log-Likelihood: -98.797
No. Observations: 23 AIC: 203.6
Df Residuals: 20 BIC: 207.0
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 712.8560 315.690 2.258 0.035 54.339 1371.373
C(dose)[T.1] 53.7098 7.949 6.757 0.000 37.128 70.292
expression -63.6539 30.505 -2.087 0.050 -127.286 -0.022
Omnibus: 1.967 Durbin-Watson: 2.064
Prob(Omnibus): 0.374 Jarque-Bera (JB): 1.085
Skew: 0.110 Prob(JB): 0.581
Kurtosis: 1.959 Cond. No. 832.

Model:
AIM ~ C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.649
Model: OLS Adj. R-squared: 0.632
Method: Least Squares F-statistic: 38.84
Date: Tue, 28 Jan 2025 Prob (F-statistic): 3.51e-06
Time: 18:40:10 Log-Likelihood: -101.06
No. Observations: 23 AIC: 206.1
Df Residuals: 21 BIC: 208.4
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 54.2083 5.919 9.159 0.000 41.900 66.517
C(dose)[T.1] 53.3371 8.558 6.232 0.000 35.539 71.135
Omnibus: 0.322 Durbin-Watson: 1.888
Prob(Omnibus): 0.851 Jarque-Bera (JB): 0.485
Skew: 0.060 Prob(JB): 0.785
Kurtosis: 2.299 Cond. No. 2.57

Model:
AIM ~ expression

OLS Regression Results
Dep. Variable: AIM R-squared: 0.054
Model: OLS Adj. R-squared: 0.009
Method: Least Squares F-statistic: 1.198
Date: Tue, 28 Jan 2025 Prob (F-statistic): 0.286
Time: 18:40:10 Log-Likelihood: -112.47
No. Observations: 23 AIC: 228.9
Df Residuals: 21 BIC: 231.2
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 690.6097 558.146 1.237 0.230 -470.118 1851.338
expression -59.0227 53.922 -1.095 0.286 -171.160 53.115
Omnibus: 3.165 Durbin-Watson: 2.508
Prob(Omnibus): 0.205 Jarque-Bera (JB): 1.353
Skew: 0.122 Prob(JB): 0.508
Kurtosis: 1.837 Cond. No. 831.

CP101

Model Comparison: AIM ~ expression + C(dose) vs AIM ~ C(dose)

F-statistic p-value df difference
0.290 0.600 1.0

Model:
AIM ~ expression + C(dose) + expression:C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.462
Model: OLS Adj. R-squared: 0.316
Method: Least Squares F-statistic: 3.152
Date: Tue, 28 Jan 2025 Prob (F-statistic): 0.0686
Time: 18:40:10 Log-Likelihood: -70.647
No. Observations: 15 AIC: 149.3
Df Residuals: 11 BIC: 152.1
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -149.1310 718.256 -0.208 0.839 -1730.001 1431.739
C(dose)[T.1] -56.4758 1037.800 -0.054 0.958 -2340.659 2227.707
expression 21.3493 70.799 0.302 0.769 -134.478 177.176
expression:C(dose)[T.1] 9.9385 101.497 0.098 0.924 -213.455 233.332
Omnibus: 1.945 Durbin-Watson: 0.888
Prob(Omnibus): 0.378 Jarque-Bera (JB): 1.522
Skew: -0.690 Prob(JB): 0.467
Kurtosis: 2.272 Cond. No. 1.75e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.462
Model: OLS Adj. R-squared: 0.372
Method: Least Squares F-statistic: 5.148
Date: Tue, 28 Jan 2025 Prob (F-statistic): 0.0243
Time: 18:40:10 Log-Likelihood: -70.654
No. Observations: 15 AIC: 147.3
Df Residuals: 12 BIC: 149.4
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -198.1834 493.027 -0.402 0.695 -1272.397 876.030
C(dose)[T.1] 45.1292 17.287 2.611 0.023 7.464 82.795
expression 26.1850 48.592 0.539 0.600 -79.687 132.057
Omnibus: 1.977 Durbin-Watson: 0.865
Prob(Omnibus): 0.372 Jarque-Bera (JB): 1.542
Skew: -0.700 Prob(JB): 0.463
Kurtosis: 2.286 Cond. No. 657.

Model:
AIM ~ C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.449
Model: OLS Adj. R-squared: 0.406
Method: Least Squares F-statistic: 10.58
Date: Tue, 28 Jan 2025 Prob (F-statistic): 0.00629
Time: 18:40:10 Log-Likelihood: -70.833
No. Observations: 15 AIC: 145.7
Df Residuals: 13 BIC: 147.1
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 67.4286 11.044 6.106 0.000 43.570 91.287
C(dose)[T.1] 49.1964 15.122 3.253 0.006 16.527 81.866
Omnibus: 2.713 Durbin-Watson: 0.810
Prob(Omnibus): 0.258 Jarque-Bera (JB): 1.868
Skew: -0.843 Prob(JB): 0.393
Kurtosis: 2.619 Cond. No. 2.70

Model:
AIM ~ expression

OLS Regression Results
Dep. Variable: AIM R-squared: 0.156
Model: OLS Adj. R-squared: 0.091
Method: Least Squares F-statistic: 2.405
Date: Tue, 28 Jan 2025 Prob (F-statistic): 0.145
Time: 18:40:11 Log-Likelihood: -74.027
No. Observations: 15 AIC: 152.1
Df Residuals: 13 BIC: 153.5
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -740.4819 537.912 -1.377 0.192 -1902.570 421.607
expression 81.5674 52.592 1.551 0.145 -32.051 195.185
Omnibus: 1.505 Durbin-Watson: 1.724
Prob(Omnibus): 0.471 Jarque-Bera (JB): 0.874
Skew: 0.155 Prob(JB): 0.646
Kurtosis: 1.859 Cond. No. 595.