LID SPN TRAP

1435928_at

6430548M08Rik RIKEN cDNA 6430548M08 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
0.039 0.846 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.691
Model: OLS Adj. R-squared: 0.642
Method: Least Squares F-statistic: 14.15
Date: Thu, 21 Nov 2024 Prob (F-statistic): 4.41e-05
Time: 05:22:49 Log-Likelihood: -99.608
No. Observations: 23 AIC: 207.2
Df Residuals: 19 BIC: 211.8
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -104.3542 161.693 -0.645 0.526 -442.781 234.072
C(dose)[T.1] 424.2053 233.200 1.819 0.085 -63.889 912.299
expression 23.5763 24.026 0.981 0.339 -26.711 73.863
expression:C(dose)[T.1] -53.7881 33.887 -1.587 0.129 -124.714 17.138
Omnibus: 0.676 Durbin-Watson: 1.994
Prob(Omnibus): 0.713 Jarque-Bera (JB): 0.693
Skew: -0.168 Prob(JB): 0.707
Kurtosis: 2.219 Cond. No. 504.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.650
Model: OLS Adj. R-squared: 0.615
Method: Least Squares F-statistic: 18.55
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.78e-05
Time: 05:22:49 Log-Likelihood: -101.04
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 77.4952 118.356 0.655 0.520 -169.391 324.381
C(dose)[T.1] 54.3820 10.242 5.310 0.000 33.019 75.745
expression -3.4625 17.575 -0.197 0.846 -40.123 33.198
Omnibus: 0.271 Durbin-Watson: 1.850
Prob(Omnibus): 0.873 Jarque-Bera (JB): 0.454
Skew: 0.058 Prob(JB): 0.797
Kurtosis: 2.322 Cond. No. 191.

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: 05:22:49 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: 0.156
Model: OLS Adj. R-squared: 0.116
Method: Least Squares F-statistic: 3.880
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0622
Time: 05:22:49 Log-Likelihood: -111.16
No. Observations: 23 AIC: 226.3
Df Residuals: 21 BIC: 228.6
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -228.4917 156.614 -1.459 0.159 -554.189 97.205
expression 44.8642 22.777 1.970 0.062 -2.503 92.232
Omnibus: 1.848 Durbin-Watson: 2.578
Prob(Omnibus): 0.397 Jarque-Bera (JB): 1.554
Skew: 0.507 Prob(JB): 0.460
Kurtosis: 2.230 Cond. No. 166.

CP101

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

F-statistic p-value df difference
0.775 0.396 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.497
Model: OLS Adj. R-squared: 0.360
Method: Least Squares F-statistic: 3.622
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0488
Time: 05:22:49 Log-Likelihood: -70.147
No. Observations: 15 AIC: 148.3
Df Residuals: 11 BIC: 151.1
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -40.7550 217.026 -0.188 0.854 -518.426 436.916
C(dose)[T.1] -223.0721 476.672 -0.468 0.649 -1272.220 826.075
expression 16.1711 32.395 0.499 0.627 -55.131 87.473
expression:C(dose)[T.1] 40.1064 70.626 0.568 0.582 -115.341 195.554
Omnibus: 0.834 Durbin-Watson: 1.025
Prob(Omnibus): 0.659 Jarque-Bera (JB): 0.708
Skew: -0.456 Prob(JB): 0.702
Kurtosis: 2.450 Cond. No. 499.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.482
Model: OLS Adj. R-squared: 0.396
Method: Least Squares F-statistic: 5.587
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0193
Time: 05:22:49 Log-Likelihood: -70.364
No. Observations: 15 AIC: 146.7
Df Residuals: 12 BIC: 148.9
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -97.2056 187.395 -0.519 0.613 -505.505 311.094
C(dose)[T.1] 47.4650 15.381 3.086 0.009 13.952 80.978
expression 24.6093 27.962 0.880 0.396 -36.315 85.533
Omnibus: 2.068 Durbin-Watson: 0.857
Prob(Omnibus): 0.356 Jarque-Bera (JB): 1.525
Skew: -0.735 Prob(JB): 0.466
Kurtosis: 2.470 Cond. No. 170.

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: 05:22:49 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: 0.071
Model: OLS Adj. R-squared: -0.000
Method: Least Squares F-statistic: 0.9979
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.336
Time: 05:22:49 Log-Likelihood: -74.745
No. Observations: 15 AIC: 153.5
Df Residuals: 13 BIC: 154.9
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -146.1383 240.256 -0.608 0.553 -665.181 372.904
expression 35.6458 35.683 0.999 0.336 -41.443 112.735
Omnibus: 0.088 Durbin-Watson: 1.780
Prob(Omnibus): 0.957 Jarque-Bera (JB): 0.306
Skew: 0.088 Prob(JB): 0.858
Kurtosis: 2.323 Cond. No. 169.