LID SPN TRAP

1456998_at

Dbpht2 DNA binding protein with his-thr domain

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
1.290 0.269 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.674
Model: OLS Adj. R-squared: 0.622
Method: Least Squares F-statistic: 13.09
Date: Tue, 03 Dec 2024 Prob (F-statistic): 7.21e-05
Time: 11:50:19 Log-Likelihood: -100.22
No. Observations: 23 AIC: 208.4
Df Residuals: 19 BIC: 213.0
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 145.2387 169.458 0.857 0.402 -209.442 499.919
C(dose)[T.1] 164.4615 252.756 0.651 0.523 -364.563 693.486
expression -20.0007 37.209 -0.538 0.597 -97.880 57.879
expression:C(dose)[T.1] -26.1489 56.704 -0.461 0.650 -144.832 92.534
Omnibus: 0.319 Durbin-Watson: 1.759
Prob(Omnibus): 0.853 Jarque-Bera (JB): 0.411
Skew: -0.237 Prob(JB): 0.814
Kurtosis: 2.549 Cond. No. 345.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.670
Model: OLS Adj. R-squared: 0.637
Method: Least Squares F-statistic: 20.33
Date: Tue, 03 Dec 2024 Prob (F-statistic): 1.52e-05
Time: 11:50:19 Log-Likelihood: -100.34
No. Observations: 23 AIC: 206.7
Df Residuals: 20 BIC: 210.1
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 196.4853 125.388 1.567 0.133 -65.070 458.041
C(dose)[T.1] 47.9935 9.715 4.940 0.000 27.729 68.258
expression -31.2603 27.519 -1.136 0.269 -88.665 26.144
Omnibus: 0.312 Durbin-Watson: 1.789
Prob(Omnibus): 0.856 Jarque-Bera (JB): 0.478
Skew: -0.181 Prob(JB): 0.788
Kurtosis: 2.393 Cond. No. 139.

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, 03 Dec 2024 Prob (F-statistic): 3.51e-06
Time: 11:50:19 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: 0.268
Model: OLS Adj. R-squared: 0.233
Method: Least Squares F-statistic: 7.690
Date: Tue, 03 Dec 2024 Prob (F-statistic): 0.0114
Time: 11:50:19 Log-Likelihood: -109.52
No. Observations: 23 AIC: 223.0
Df Residuals: 21 BIC: 225.3
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 513.6776 156.617 3.280 0.004 187.976 839.379
expression -97.0914 35.013 -2.773 0.011 -169.905 -24.278
Omnibus: 1.604 Durbin-Watson: 1.872
Prob(Omnibus): 0.448 Jarque-Bera (JB): 0.995
Skew: -0.121 Prob(JB): 0.608
Kurtosis: 2.010 Cond. No. 119.

CP101

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

F-statistic p-value df difference
0.008 0.929 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.461
Model: OLS Adj. R-squared: 0.314
Method: Least Squares F-statistic: 3.133
Date: Tue, 03 Dec 2024 Prob (F-statistic): 0.0695
Time: 11:50:19 Log-Likelihood: -70.668
No. Observations: 15 AIC: 149.3
Df Residuals: 11 BIC: 152.2
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -41.2559 294.161 -0.140 0.891 -688.700 606.188
C(dose)[T.1] 214.6093 341.267 0.629 0.542 -536.515 965.734
expression 25.5605 69.125 0.370 0.719 -126.582 177.703
expression:C(dose)[T.1] -39.4465 81.021 -0.487 0.636 -217.771 138.878
Omnibus: 3.269 Durbin-Watson: 0.818
Prob(Omnibus): 0.195 Jarque-Bera (JB): 2.239
Skew: -0.931 Prob(JB): 0.326
Kurtosis: 2.664 Cond. No. 272.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.449
Model: OLS Adj. R-squared: 0.357
Method: Least Squares F-statistic: 4.892
Date: Tue, 03 Dec 2024 Prob (F-statistic): 0.0279
Time: 11:50:19 Log-Likelihood: -70.828
No. Observations: 15 AIC: 147.7
Df Residuals: 12 BIC: 149.8
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 80.8349 148.806 0.543 0.597 -243.387 405.056
C(dose)[T.1] 48.6707 16.775 2.901 0.013 12.120 85.221
expression -3.1529 34.892 -0.090 0.929 -79.176 72.870
Omnibus: 2.702 Durbin-Watson: 0.805
Prob(Omnibus): 0.259 Jarque-Bera (JB): 1.880
Skew: -0.844 Prob(JB): 0.391
Kurtosis: 2.597 Cond. No. 84.2

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, 03 Dec 2024 Prob (F-statistic): 0.00629
Time: 11:50:19 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: 0.063
Model: OLS Adj. R-squared: -0.009
Method: Least Squares F-statistic: 0.8702
Date: Tue, 03 Dec 2024 Prob (F-statistic): 0.368
Time: 11:50:20 Log-Likelihood: -74.814
No. Observations: 15 AIC: 153.6
Df Residuals: 13 BIC: 155.0
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 252.9471 171.030 1.479 0.163 -116.540 622.434
expression -38.2599 41.014 -0.933 0.368 -126.865 50.346
Omnibus: 0.959 Durbin-Watson: 1.616
Prob(Omnibus): 0.619 Jarque-Bera (JB): 0.695
Skew: 0.017 Prob(JB): 0.706
Kurtosis: 1.946 Cond. No. 76.7