LID SPN TRAP

1434868_at

4933431E20Rik RIKEN cDNA 4933431E20 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
0.000 0.996 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.676
Model: OLS Adj. R-squared: 0.625
Method: Least Squares F-statistic: 13.20
Date: Thu, 21 Nov 2024 Prob (F-statistic): 6.84e-05
Time: 04:40:06 Log-Likelihood: -100.15
No. Observations: 23 AIC: 208.3
Df Residuals: 19 BIC: 212.8
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -82.9622 187.202 -0.443 0.663 -474.781 308.857
C(dose)[T.1] 455.4510 321.357 1.417 0.173 -217.157 1128.059
expression 15.1953 20.727 0.733 0.472 -28.187 58.578
expression:C(dose)[T.1] -44.5779 35.612 -1.252 0.226 -119.116 29.960
Omnibus: 1.720 Durbin-Watson: 1.846
Prob(Omnibus): 0.423 Jarque-Bera (JB): 1.051
Skew: -0.159 Prob(JB): 0.591
Kurtosis: 2.002 Cond. No. 823.

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: 18.49
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.83e-05
Time: 04:40:06 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 53.3528 154.411 0.346 0.733 -268.743 375.449
C(dose)[T.1] 53.3381 8.772 6.081 0.000 35.041 71.635
expression 0.0948 17.092 0.006 0.996 -35.558 35.748
Omnibus: 0.323 Durbin-Watson: 1.887
Prob(Omnibus): 0.851 Jarque-Bera (JB): 0.486
Skew: 0.059 Prob(JB): 0.784
Kurtosis: 2.298 Cond. No. 322.

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: 04:40:06 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: 0.000
Model: OLS Adj. R-squared: -0.047
Method: Least Squares F-statistic: 0.004851
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.945
Time: 04:40:06 Log-Likelihood: -113.10
No. Observations: 23 AIC: 230.2
Df Residuals: 21 BIC: 232.5
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 97.4050 254.060 0.383 0.705 -430.942 625.752
expression -1.9604 28.148 -0.070 0.945 -60.497 56.576
Omnibus: 3.435 Durbin-Watson: 2.486
Prob(Omnibus): 0.180 Jarque-Bera (JB): 1.580
Skew: 0.280 Prob(JB): 0.454
Kurtosis: 1.844 Cond. No. 322.

CP101

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

F-statistic p-value df difference
0.595 0.456 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.548
Model: OLS Adj. R-squared: 0.425
Method: Least Squares F-statistic: 4.449
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0280
Time: 04:40:06 Log-Likelihood: -69.341
No. Observations: 15 AIC: 146.7
Df Residuals: 11 BIC: 149.5
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -36.5826 317.264 -0.115 0.910 -734.876 661.711
C(dose)[T.1] 692.3675 475.829 1.455 0.174 -354.924 1739.659
expression 11.5946 35.346 0.328 0.749 -66.202 89.391
expression:C(dose)[T.1] -69.3614 51.882 -1.337 0.208 -183.554 44.831
Omnibus: 0.977 Durbin-Watson: 0.845
Prob(Omnibus): 0.613 Jarque-Bera (JB): 0.852
Skew: -0.486 Prob(JB): 0.653
Kurtosis: 2.355 Cond. No. 778.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.475
Model: OLS Adj. R-squared: 0.387
Method: Least Squares F-statistic: 5.424
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0210
Time: 04:40:06 Log-Likelihood: -70.470
No. Observations: 15 AIC: 146.9
Df Residuals: 12 BIC: 149.1
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 252.2105 239.866 1.051 0.314 -270.412 774.833
C(dose)[T.1] 56.6681 18.163 3.120 0.009 17.094 96.242
expression -20.5985 26.710 -0.771 0.456 -78.794 37.597
Omnibus: 3.068 Durbin-Watson: 0.739
Prob(Omnibus): 0.216 Jarque-Bera (JB): 2.145
Skew: -0.905 Prob(JB): 0.342
Kurtosis: 2.603 Cond. No. 291.

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: 04:40:06 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: 0.049
Model: OLS Adj. R-squared: -0.024
Method: Least Squares F-statistic: 0.6667
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.429
Time: 04:40:06 Log-Likelihood: -74.925
No. Observations: 15 AIC: 153.8
Df Residuals: 13 BIC: 155.3
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -124.9124 267.887 -0.466 0.649 -703.647 453.822
expression 23.8516 29.212 0.816 0.429 -39.257 86.961
Omnibus: 1.004 Durbin-Watson: 1.317
Prob(Omnibus): 0.605 Jarque-Bera (JB): 0.749
Skew: 0.179 Prob(JB): 0.688
Kurtosis: 1.966 Cond. No. 251.