LID SPN TRAP

1416505_at

Nr4a1 nuclear receptor subfamily 4, group A, member 1

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
0.089 0.769 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.705
Model: OLS Adj. R-squared: 0.658
Method: Least Squares F-statistic: 15.13
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.84e-05
Time: 06:20:40 Log-Likelihood: -99.066
No. Observations: 23 AIC: 206.1
Df Residuals: 19 BIC: 210.7
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 125.1799 75.341 1.662 0.113 -32.511 282.870
C(dose)[T.1] -380.1824 232.860 -1.633 0.119 -867.564 107.200
expression -7.5603 8.003 -0.945 0.357 -24.310 9.190
expression:C(dose)[T.1] 43.2359 23.104 1.871 0.077 -5.121 91.593
Omnibus: 4.830 Durbin-Watson: 1.918
Prob(Omnibus): 0.089 Jarque-Bera (JB): 1.582
Skew: -0.003 Prob(JB): 0.453
Kurtosis: 1.715 Cond. No. 647.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.651
Model: OLS Adj. R-squared: 0.616
Method: Least Squares F-statistic: 18.62
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.71e-05
Time: 06:20:40 Log-Likelihood: -101.01
No. Observations: 23 AIC: 208.0
Df Residuals: 20 BIC: 211.4
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 76.4838 74.997 1.020 0.320 -79.957 232.925
C(dose)[T.1] 55.1759 10.707 5.153 0.000 32.841 77.511
expression -2.3729 7.963 -0.298 0.769 -18.984 14.238
Omnibus: 0.326 Durbin-Watson: 1.943
Prob(Omnibus): 0.849 Jarque-Bera (JB): 0.486
Skew: 0.004 Prob(JB): 0.784
Kurtosis: 2.288 Cond. No. 170.

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: Thu, 21 Nov 2024 Prob (F-statistic): 3.51e-06
Time: 06:20:40 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: 0.187
Model: OLS Adj. R-squared: 0.148
Method: Least Squares F-statistic: 4.821
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0395
Time: 06:20:40 Log-Likelihood: -110.73
No. Observations: 23 AIC: 225.5
Df Residuals: 21 BIC: 227.7
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -127.8878 94.773 -1.349 0.192 -324.978 69.203
expression 21.2753 9.689 2.196 0.039 1.125 41.425
Omnibus: 3.582 Durbin-Watson: 2.123
Prob(Omnibus): 0.167 Jarque-Bera (JB): 1.406
Skew: 0.082 Prob(JB): 0.495
Kurtosis: 1.800 Cond. No. 144.

CP101

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

F-statistic p-value df difference
2.895 0.115 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.556
Model: OLS Adj. R-squared: 0.435
Method: Least Squares F-statistic: 4.590
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0256
Time: 06:20:40 Log-Likelihood: -69.212
No. Observations: 15 AIC: 146.4
Df Residuals: 11 BIC: 149.3
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 320.8039 293.712 1.092 0.298 -325.652 967.260
C(dose)[T.1] 44.1255 344.498 0.128 0.900 -714.110 802.361
expression -28.8390 33.408 -0.863 0.406 -102.369 44.691
expression:C(dose)[T.1] 0.1943 39.320 0.005 0.996 -86.349 86.737
Omnibus: 2.061 Durbin-Watson: 0.876
Prob(Omnibus): 0.357 Jarque-Bera (JB): 1.585
Skew: -0.672 Prob(JB): 0.453
Kurtosis: 2.145 Cond. No. 607.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.556
Model: OLS Adj. R-squared: 0.482
Method: Least Squares F-statistic: 7.510
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00767
Time: 06:20:40 Log-Likelihood: -69.212
No. Observations: 15 AIC: 144.4
Df Residuals: 12 BIC: 146.5
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 319.5715 148.561 2.151 0.053 -4.114 643.257
C(dose)[T.1] 45.8265 14.266 3.212 0.007 14.744 76.909
expression -28.6988 16.868 -1.701 0.115 -65.452 8.054
Omnibus: 2.058 Durbin-Watson: 0.875
Prob(Omnibus): 0.357 Jarque-Bera (JB): 1.583
Skew: -0.671 Prob(JB): 0.453
Kurtosis: 2.146 Cond. No. 187.

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: Thu, 21 Nov 2024 Prob (F-statistic): 0.00629
Time: 06:20:40 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: 0.174
Model: OLS Adj. R-squared: 0.110
Method: Least Squares F-statistic: 2.739
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.122
Time: 06:20:40 Log-Likelihood: -73.866
No. Observations: 15 AIC: 151.7
Df Residuals: 13 BIC: 153.1
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 409.6418 191.158 2.143 0.052 -3.330 822.614
expression -36.2223 21.888 -1.655 0.122 -83.509 11.064
Omnibus: 0.107 Durbin-Watson: 1.804
Prob(Omnibus): 0.948 Jarque-Bera (JB): 0.269
Skew: 0.157 Prob(JB): 0.874
Kurtosis: 2.425 Cond. No. 183.