LID SPN TRAP

1448390_a_at

Dhrs3 dehydrogenase/reductase (SDR family) 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
0.788 0.385 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.664
Model: OLS Adj. R-squared: 0.611
Method: Least Squares F-statistic: 12.51
Date: Thu, 03 Apr 2025 Prob (F-statistic): 9.55e-05
Time: 23:01:29 Log-Likelihood: -100.56
No. Observations: 23 AIC: 209.1
Df Residuals: 19 BIC: 213.7
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 84.7968 79.674 1.064 0.301 -81.962 251.556
C(dose)[T.1] 84.6771 109.188 0.776 0.448 -143.856 313.210
expression -5.2504 13.636 -0.385 0.704 -33.790 23.289
expression:C(dose)[T.1] -5.6564 18.910 -0.299 0.768 -45.235 33.922
Omnibus: 0.395 Durbin-Watson: 1.972
Prob(Omnibus): 0.821 Jarque-Bera (JB): 0.136
Skew: -0.183 Prob(JB): 0.934
Kurtosis: 2.910 Cond. No. 193.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.662
Model: OLS Adj. R-squared: 0.629
Method: Least Squares F-statistic: 19.62
Date: Thu, 03 Apr 2025 Prob (F-statistic): 1.93e-05
Time: 23:01:29 Log-Likelihood: -100.62
No. Observations: 23 AIC: 207.2
Df Residuals: 20 BIC: 210.6
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 101.9320 54.100 1.884 0.074 -10.918 214.782
C(dose)[T.1] 52.1252 8.710 5.985 0.000 33.957 70.293
expression -8.1916 9.230 -0.888 0.385 -27.444 11.061
Omnibus: 0.175 Durbin-Watson: 1.980
Prob(Omnibus): 0.916 Jarque-Bera (JB): 0.179
Skew: -0.161 Prob(JB): 0.915
Kurtosis: 2.711 Cond. No. 75.1

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, 03 Apr 2025 Prob (F-statistic): 3.51e-06
Time: 23:01:29 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: 0.058
Model: OLS Adj. R-squared: 0.013
Method: Least Squares F-statistic: 1.286
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.270
Time: 23:01:29 Log-Likelihood: -112.42
No. Observations: 23 AIC: 228.8
Df Residuals: 21 BIC: 231.1
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 176.7024 85.815 2.059 0.052 -1.760 355.165
expression -16.8518 14.861 -1.134 0.270 -47.757 14.054
Omnibus: 2.359 Durbin-Watson: 2.650
Prob(Omnibus): 0.307 Jarque-Bera (JB): 1.196
Skew: 0.138 Prob(JB): 0.550
Kurtosis: 1.917 Cond. No. 72.8

CP101

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

F-statistic p-value df difference
1.484 0.247 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.519
Model: OLS Adj. R-squared: 0.388
Method: Least Squares F-statistic: 3.960
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.0386
Time: 23:01:30 Log-Likelihood: -69.807
No. Observations: 15 AIC: 147.6
Df Residuals: 11 BIC: 150.4
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -126.7463 162.260 -0.781 0.451 -483.879 230.386
C(dose)[T.1] 166.7698 245.378 0.680 0.511 -373.304 706.843
expression 27.1837 22.662 1.200 0.256 -22.694 77.061
expression:C(dose)[T.1] -16.3496 34.484 -0.474 0.645 -92.247 59.548
Omnibus: 2.731 Durbin-Watson: 0.898
Prob(Omnibus): 0.255 Jarque-Bera (JB): 1.736
Skew: -0.825 Prob(JB): 0.420
Kurtosis: 2.765 Cond. No. 300.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.509
Model: OLS Adj. R-squared: 0.428
Method: Least Squares F-statistic: 6.231
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.0139
Time: 23:01:30 Log-Likelihood: -69.959
No. Observations: 15 AIC: 145.9
Df Residuals: 12 BIC: 148.0
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -76.3100 118.501 -0.644 0.532 -334.501 181.881
C(dose)[T.1] 50.6591 14.897 3.401 0.005 18.202 83.117
expression 20.1228 16.520 1.218 0.247 -15.871 56.117
Omnibus: 2.666 Durbin-Watson: 0.764
Prob(Omnibus): 0.264 Jarque-Bera (JB): 1.664
Skew: -0.809 Prob(JB): 0.435
Kurtosis: 2.788 Cond. No. 116.

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, 03 Apr 2025 Prob (F-statistic): 0.00629
Time: 23:01:30 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: 0.037
Model: OLS Adj. R-squared: -0.037
Method: Least Squares F-statistic: 0.4948
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.494
Time: 23:01:30 Log-Likelihood: -75.020
No. Observations: 15 AIC: 154.0
Df Residuals: 13 BIC: 155.5
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -17.1196 157.813 -0.108 0.915 -358.053 323.814
expression 15.5943 22.169 0.703 0.494 -32.300 63.488
Omnibus: 1.841 Durbin-Watson: 1.669
Prob(Omnibus): 0.398 Jarque-Bera (JB): 0.986
Skew: 0.215 Prob(JB): 0.611
Kurtosis: 1.820 Cond. No. 115.