LID SPN TRAP

1447863_s_at

Nr4a2 nuclear receptor subfamily 4, group A, member 2

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
0.011 0.917 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.693
Model: OLS Adj. R-squared: 0.645
Method: Least Squares F-statistic: 14.30
Date: Tue, 28 Jan 2025 Prob (F-statistic): 4.12e-05
Time: 17:31:41 Log-Likelihood: -99.524
No. Observations: 23 AIC: 207.0
Df Residuals: 19 BIC: 211.6
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -18.5586 103.612 -0.179 0.860 -235.422 198.305
C(dose)[T.1] 583.2168 323.567 1.802 0.087 -94.018 1260.451
expression 7.6204 10.834 0.703 0.490 -15.054 30.295
expression:C(dose)[T.1] -48.8042 29.661 -1.645 0.116 -110.885 13.276
Omnibus: 1.303 Durbin-Watson: 1.833
Prob(Omnibus): 0.521 Jarque-Bera (JB): 1.101
Skew: 0.495 Prob(JB): 0.577
Kurtosis: 2.589 Cond. No. 945.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.649
Model: OLS Adj. R-squared: 0.614
Method: Least Squares F-statistic: 18.51
Date: Tue, 28 Jan 2025 Prob (F-statistic): 2.82e-05
Time: 17:31:41 Log-Likelihood: -101.06
No. Observations: 23 AIC: 208.1
Df Residuals: 20 BIC: 211.5
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 43.6125 100.511 0.434 0.669 -166.050 253.275
C(dose)[T.1] 51.6168 18.499 2.790 0.011 13.028 90.205
expression 1.1096 10.507 0.106 0.917 -20.807 23.026
Omnibus: 0.249 Durbin-Watson: 1.896
Prob(Omnibus): 0.883 Jarque-Bera (JB): 0.439
Skew: 0.075 Prob(JB): 0.803
Kurtosis: 2.340 Cond. No. 243.

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: 17:31:41 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: 0.513
Model: OLS Adj. R-squared: 0.490
Method: Least Squares F-statistic: 22.10
Date: Tue, 28 Jan 2025 Prob (F-statistic): 0.000122
Time: 17:31:41 Log-Likelihood: -104.84
No. Observations: 23 AIC: 213.7
Df Residuals: 21 BIC: 215.9
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -197.3448 59.156 -3.336 0.003 -320.367 -74.323
expression 26.9243 5.728 4.701 0.000 15.013 38.836
Omnibus: 1.045 Durbin-Watson: 2.081
Prob(Omnibus): 0.593 Jarque-Bera (JB): 0.810
Skew: 0.435 Prob(JB): 0.667
Kurtosis: 2.704 Cond. No. 122.

CP101

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

F-statistic p-value df difference
0.198 0.664 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.488
Model: OLS Adj. R-squared: 0.348
Method: Least Squares F-statistic: 3.493
Date: Tue, 28 Jan 2025 Prob (F-statistic): 0.0535
Time: 17:31:41 Log-Likelihood: -70.281
No. Observations: 15 AIC: 148.6
Df Residuals: 11 BIC: 151.4
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 94.2221 115.503 0.816 0.432 -159.999 348.444
C(dose)[T.1] -95.9537 176.874 -0.542 0.598 -485.250 293.343
expression -3.8129 16.354 -0.233 0.820 -39.808 32.182
expression:C(dose)[T.1] 19.2039 23.852 0.805 0.438 -33.293 71.701
Omnibus: 2.378 Durbin-Watson: 0.948
Prob(Omnibus): 0.304 Jarque-Bera (JB): 1.354
Skew: -0.734 Prob(JB): 0.508
Kurtosis: 2.886 Cond. No. 222.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.458
Model: OLS Adj. R-squared: 0.367
Method: Least Squares F-statistic: 5.064
Date: Tue, 28 Jan 2025 Prob (F-statistic): 0.0254
Time: 17:31:41 Log-Likelihood: -70.710
No. Observations: 15 AIC: 147.4
Df Residuals: 12 BIC: 149.5
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 30.7791 83.204 0.370 0.718 -150.507 212.066
C(dose)[T.1] 45.7395 17.440 2.623 0.022 7.741 83.738
expression 5.2154 11.729 0.445 0.664 -20.339 30.770
Omnibus: 3.139 Durbin-Watson: 0.880
Prob(Omnibus): 0.208 Jarque-Bera (JB): 2.000
Skew: -0.889 Prob(JB): 0.368
Kurtosis: 2.798 Cond. No. 81.2

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, 28 Jan 2025 Prob (F-statistic): 0.00629
Time: 17:31:41 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: 0.147
Model: OLS Adj. R-squared: 0.081
Method: Least Squares F-statistic: 2.238
Date: Tue, 28 Jan 2025 Prob (F-statistic): 0.159
Time: 17:31:41 Log-Likelihood: -74.109
No. Observations: 15 AIC: 152.2
Df Residuals: 13 BIC: 153.6
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -46.0289 93.850 -0.490 0.632 -248.780 156.722
expression 18.9273 12.652 1.496 0.159 -8.406 46.260
Omnibus: 0.674 Durbin-Watson: 1.636
Prob(Omnibus): 0.714 Jarque-Bera (JB): 0.298
Skew: -0.333 Prob(JB): 0.862
Kurtosis: 2.814 Cond. No. 75.5