LID SPN TRAP

1448250_at

9030425E11Rik RIKEN cDNA 9030425E11 gene

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
0.012 0.914 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.657
Model: OLS Adj. R-squared: 0.603
Method: Least Squares F-statistic: 12.16
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.000114
Time: 22:48:42 Log-Likelihood: -100.78
No. Observations: 23 AIC: 209.6
Df Residuals: 19 BIC: 214.1
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 5.6593 100.015 0.057 0.955 -203.674 214.992
C(dose)[T.1] 173.6035 180.400 0.962 0.348 -203.977 551.185
expression 6.7272 13.832 0.486 0.632 -22.224 35.678
expression:C(dose)[T.1] -15.6961 23.307 -0.673 0.509 -64.479 33.087
Omnibus: 0.332 Durbin-Watson: 1.832
Prob(Omnibus): 0.847 Jarque-Bera (JB): 0.495
Skew: -0.114 Prob(JB): 0.781
Kurtosis: 2.318 Cond. No. 385.

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: Thu, 03 Apr 2025 Prob (F-statistic): 2.82e-05
Time: 22:48:42 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 45.5567 79.471 0.573 0.573 -120.217 211.331
C(dose)[T.1] 52.4029 12.251 4.277 0.000 26.848 77.958
expression 1.1988 10.980 0.109 0.914 -21.705 24.102
Omnibus: 0.302 Durbin-Watson: 1.896
Prob(Omnibus): 0.860 Jarque-Bera (JB): 0.473
Skew: 0.050 Prob(JB): 0.790
Kurtosis: 2.305 Cond. No. 142.

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: 22:48:42 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: 0.328
Model: OLS Adj. R-squared: 0.296
Method: Least Squares F-statistic: 10.27
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.00426
Time: 22:48:42 Log-Likelihood: -108.53
No. Observations: 23 AIC: 221.1
Df Residuals: 21 BIC: 223.3
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -178.3504 80.751 -2.209 0.038 -346.280 -10.420
expression 34.0029 10.611 3.204 0.004 11.936 56.070
Omnibus: 0.336 Durbin-Watson: 2.222
Prob(Omnibus): 0.845 Jarque-Bera (JB): 0.271
Skew: 0.230 Prob(JB): 0.873
Kurtosis: 2.732 Cond. No. 106.

CP101

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

F-statistic p-value df difference
3.594 0.082 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.628
Model: OLS Adj. R-squared: 0.526
Method: Least Squares F-statistic: 6.189
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.0102
Time: 22:48:42 Log-Likelihood: -67.885
No. Observations: 15 AIC: 143.8
Df Residuals: 11 BIC: 146.6
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 12.0553 195.913 0.062 0.952 -419.147 443.258
C(dose)[T.1] -267.2948 254.893 -1.049 0.317 -828.310 293.721
expression 7.6925 27.182 0.283 0.782 -52.135 67.520
expression:C(dose)[T.1] 43.8756 35.335 1.242 0.240 -33.895 121.646
Omnibus: 11.806 Durbin-Watson: 1.083
Prob(Omnibus): 0.003 Jarque-Bera (JB): 7.925
Skew: -1.576 Prob(JB): 0.0190
Kurtosis: 4.655 Cond. No. 385.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.576
Model: OLS Adj. R-squared: 0.505
Method: Least Squares F-statistic: 8.144
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.00583
Time: 22:48:42 Log-Likelihood: -68.868
No. Observations: 15 AIC: 143.7
Df Residuals: 12 BIC: 145.9
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -174.8481 128.203 -1.364 0.198 -454.178 104.481
C(dose)[T.1] 48.7657 13.809 3.531 0.004 18.678 78.854
expression 33.6573 17.755 1.896 0.082 -5.027 72.342
Omnibus: 8.642 Durbin-Watson: 0.874
Prob(Omnibus): 0.013 Jarque-Bera (JB): 5.348
Skew: -1.394 Prob(JB): 0.0690
Kurtosis: 3.886 Cond. No. 137.

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: 22:48:43 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: 0.135
Model: OLS Adj. R-squared: 0.068
Method: Least Squares F-statistic: 2.028
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.178
Time: 22:48:43 Log-Likelihood: -74.213
No. Observations: 15 AIC: 152.4
Df Residuals: 13 BIC: 153.8
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -156.2733 175.744 -0.889 0.390 -535.946 223.399
expression 34.6890 24.356 1.424 0.178 -17.929 87.307
Omnibus: 0.855 Durbin-Watson: 2.171
Prob(Omnibus): 0.652 Jarque-Bera (JB): 0.787
Skew: -0.444 Prob(JB): 0.675
Kurtosis: 2.312 Cond. No. 137.