LID SPN TRAP

1456798_at

9330118A15Rik RIKEN cDNA 9330118A15 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
1.570 0.225 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.687
Model: OLS Adj. R-squared: 0.637
Method: Least Squares F-statistic: 13.88
Date: Thu, 21 Nov 2024 Prob (F-statistic): 4.98e-05
Time: 05:11:16 Log-Likelihood: -99.759
No. Observations: 23 AIC: 207.5
Df Residuals: 19 BIC: 212.1
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 222.0391 112.466 1.974 0.063 -13.355 457.433
C(dose)[T.1] -87.7069 166.891 -0.526 0.605 -437.014 261.600
expression -24.2320 16.216 -1.494 0.152 -58.173 9.709
expression:C(dose)[T.1] 20.4190 23.881 0.855 0.403 -29.564 70.401
Omnibus: 0.801 Durbin-Watson: 1.571
Prob(Omnibus): 0.670 Jarque-Bera (JB): 0.791
Skew: -0.245 Prob(JB): 0.673
Kurtosis: 2.235 Cond. No. 357.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.675
Model: OLS Adj. R-squared: 0.642
Method: Least Squares F-statistic: 20.73
Date: Thu, 21 Nov 2024 Prob (F-statistic): 1.33e-05
Time: 05:11:16 Log-Likelihood: -100.19
No. Observations: 23 AIC: 206.4
Df Residuals: 20 BIC: 209.8
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 156.8285 82.099 1.910 0.071 -14.428 328.085
C(dose)[T.1] 54.8040 8.525 6.428 0.000 37.020 72.588
expression -14.8167 11.824 -1.253 0.225 -39.481 9.847
Omnibus: 0.723 Durbin-Watson: 1.650
Prob(Omnibus): 0.697 Jarque-Bera (JB): 0.762
Skew: -0.339 Prob(JB): 0.683
Kurtosis: 2.421 Cond. No. 139.

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: 05:11:16 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: 0.002
Model: OLS Adj. R-squared: -0.045
Method: Least Squares F-statistic: 0.04791
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.829
Time: 05:11:16 Log-Likelihood: -113.08
No. Observations: 23 AIC: 230.2
Df Residuals: 21 BIC: 232.4
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 110.2652 139.749 0.789 0.439 -180.358 400.889
expression -4.3807 20.014 -0.219 0.829 -46.002 37.240
Omnibus: 3.629 Durbin-Watson: 2.460
Prob(Omnibus): 0.163 Jarque-Bera (JB): 1.645
Skew: 0.297 Prob(JB): 0.439
Kurtosis: 1.832 Cond. No. 138.

CP101

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

F-statistic p-value df difference
0.196 0.666 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: 3.522
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0524
Time: 05:11:16 Log-Likelihood: -70.250
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 108.6051 167.672 0.648 0.530 -260.439 477.649
C(dose)[T.1] -144.6865 237.477 -0.609 0.555 -667.370 377.997
expression -6.2284 25.302 -0.246 0.810 -61.918 49.461
expression:C(dose)[T.1] 31.0962 37.244 0.835 0.422 -50.877 113.069
Omnibus: 5.196 Durbin-Watson: 0.935
Prob(Omnibus): 0.074 Jarque-Bera (JB): 2.893
Skew: -1.057 Prob(JB): 0.235
Kurtosis: 3.396 Cond. No. 257.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.458
Model: OLS Adj. R-squared: 0.367
Method: Least Squares F-statistic: 5.063
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0254
Time: 05:11:16 Log-Likelihood: -70.711
No. Observations: 15 AIC: 147.4
Df Residuals: 12 BIC: 149.5
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 13.7228 121.722 0.113 0.912 -251.487 278.933
C(dose)[T.1] 53.0175 17.835 2.973 0.012 14.158 91.877
expression 8.1236 18.331 0.443 0.666 -31.816 48.063
Omnibus: 3.224 Durbin-Watson: 0.971
Prob(Omnibus): 0.200 Jarque-Bera (JB): 2.007
Skew: -0.893 Prob(JB): 0.367
Kurtosis: 2.849 Cond. No. 103.

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: 05:11:16 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: 0.058
Model: OLS Adj. R-squared: -0.014
Method: Least Squares F-statistic: 0.8044
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.386
Time: 05:11:16 Log-Likelihood: -74.850
No. Observations: 15 AIC: 153.7
Df Residuals: 13 BIC: 155.1
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 209.5500 129.584 1.617 0.130 -70.400 489.500
expression -18.2200 20.315 -0.897 0.386 -62.108 25.668
Omnibus: 1.350 Durbin-Watson: 1.275
Prob(Omnibus): 0.509 Jarque-Bera (JB): 0.810
Skew: 0.080 Prob(JB): 0.667
Kurtosis: 1.873 Cond. No. 85.9