LID SPN TRAP

1438796_at

Nr4a3 nuclear receptor subfamily 4, group A, member 3

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
1.037 0.321 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.700
Model: OLS Adj. R-squared: 0.652
Method: Least Squares F-statistic: 14.76
Date: Thu, 21 Nov 2024 Prob (F-statistic): 3.35e-05
Time: 06:21:48 Log-Likelihood: -99.270
No. Observations: 23 AIC: 206.5
Df Residuals: 19 BIC: 211.1
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 160.7584 342.505 0.469 0.644 -556.114 877.631
C(dose)[T.1] 1235.1436 807.071 1.530 0.142 -454.076 2924.363
expression -9.3402 30.020 -0.311 0.759 -72.173 53.492
expression:C(dose)[T.1] -100.3421 69.077 -1.453 0.163 -244.922 44.237
Omnibus: 0.514 Durbin-Watson: 1.826
Prob(Omnibus): 0.773 Jarque-Bera (JB): 0.610
Skew: 0.163 Prob(JB): 0.737
Kurtosis: 2.272 Cond. No. 2.63e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.666
Model: OLS Adj. R-squared: 0.633
Method: Least Squares F-statistic: 19.97
Date: Thu, 21 Nov 2024 Prob (F-statistic): 1.71e-05
Time: 06:21:48 Log-Likelihood: -100.48
No. Observations: 23 AIC: 207.0
Df Residuals: 20 BIC: 210.4
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 376.9479 316.926 1.189 0.248 -284.148 1038.044
C(dose)[T.1] 62.9164 12.711 4.950 0.000 36.401 89.431
expression -28.2915 27.777 -1.019 0.321 -86.233 29.650
Omnibus: 1.289 Durbin-Watson: 2.006
Prob(Omnibus): 0.525 Jarque-Bera (JB): 0.873
Skew: 0.033 Prob(JB): 0.646
Kurtosis: 2.048 Cond. No. 866.

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: 06:21:48 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: 0.258
Model: OLS Adj. R-squared: 0.222
Method: Least Squares F-statistic: 7.289
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0134
Time: 06:21:48 Log-Likelihood: -109.68
No. Observations: 23 AIC: 223.4
Df Residuals: 21 BIC: 225.6
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -769.9201 314.762 -2.446 0.023 -1424.503 -115.337
expression 73.4371 27.201 2.700 0.013 16.870 130.004
Omnibus: 1.046 Durbin-Watson: 2.063
Prob(Omnibus): 0.593 Jarque-Bera (JB): 0.835
Skew: 0.151 Prob(JB): 0.659
Kurtosis: 2.117 Cond. No. 590.

CP101

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

F-statistic p-value df difference
0.480 0.502 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.490
Model: OLS Adj. R-squared: 0.351
Method: Least Squares F-statistic: 3.525
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0523
Time: 06:21:48 Log-Likelihood: -70.248
No. Observations: 15 AIC: 148.5
Df Residuals: 11 BIC: 151.3
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 321.1638 269.072 1.194 0.258 -271.060 913.387
C(dose)[T.1] -215.4513 395.349 -0.545 0.597 -1085.609 654.707
expression -26.5951 28.177 -0.944 0.366 -88.612 35.421
expression:C(dose)[T.1] 27.7756 42.123 0.659 0.523 -64.936 120.487
Omnibus: 3.474 Durbin-Watson: 0.995
Prob(Omnibus): 0.176 Jarque-Bera (JB): 2.192
Skew: -0.933 Prob(JB): 0.334
Kurtosis: 2.851 Cond. No. 618.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.470
Model: OLS Adj. R-squared: 0.382
Method: Least Squares F-statistic: 5.320
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0222
Time: 06:21:48 Log-Likelihood: -70.539
No. Observations: 15 AIC: 147.1
Df Residuals: 12 BIC: 149.2
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 202.5894 195.389 1.037 0.320 -223.126 628.305
C(dose)[T.1] 45.0007 16.579 2.714 0.019 8.878 81.124
expression -14.1668 20.445 -0.693 0.502 -58.714 30.380
Omnibus: 4.050 Durbin-Watson: 0.799
Prob(Omnibus): 0.132 Jarque-Bera (JB): 2.678
Skew: -1.031 Prob(JB): 0.262
Kurtosis: 2.817 Cond. No. 241.

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: 06:21:48 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: 0.145
Model: OLS Adj. R-squared: 0.079
Method: Least Squares F-statistic: 2.197
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.162
Time: 06:21:48 Log-Likelihood: -74.129
No. Observations: 15 AIC: 152.3
Df Residuals: 13 BIC: 153.7
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 416.7607 218.174 1.910 0.078 -54.576 888.098
expression -34.4350 23.231 -1.482 0.162 -84.623 15.753
Omnibus: 1.554 Durbin-Watson: 1.662
Prob(Omnibus): 0.460 Jarque-Bera (JB): 0.849
Skew: 0.010 Prob(JB): 0.654
Kurtosis: 1.835 Cond. No. 220.