LID SPN TRAP

1435935_at

2410131K14Rik RIKEN cDNA 2410131K14 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
3.353 0.082 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.700
Model: OLS Adj. R-squared: 0.653
Method: Least Squares F-statistic: 14.81
Date: Thu, 21 Nov 2024 Prob (F-statistic): 3.28e-05
Time: 05:08:06 Log-Likelihood: -99.242
No. Observations: 23 AIC: 206.5
Df Residuals: 19 BIC: 211.0
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -50.0469 115.471 -0.433 0.670 -291.730 191.636
C(dose)[T.1] 29.7309 141.640 0.210 0.836 -266.726 326.187
expression 13.5718 15.013 0.904 0.377 -17.851 44.995
expression:C(dose)[T.1] 4.8264 19.078 0.253 0.803 -35.104 44.757
Omnibus: 0.290 Durbin-Watson: 1.659
Prob(Omnibus): 0.865 Jarque-Bera (JB): 0.465
Skew: -0.042 Prob(JB): 0.792
Kurtosis: 2.308 Cond. No. 349.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.699
Model: OLS Adj. R-squared: 0.669
Method: Least Squares F-statistic: 23.27
Date: Thu, 21 Nov 2024 Prob (F-statistic): 6.02e-06
Time: 05:08:06 Log-Likelihood: -99.280
No. Observations: 23 AIC: 204.6
Df Residuals: 20 BIC: 208.0
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -73.0071 69.701 -1.047 0.307 -218.400 72.386
C(dose)[T.1] 65.4610 10.474 6.250 0.000 43.613 87.310
expression 16.5607 9.044 1.831 0.082 -2.305 35.426
Omnibus: 0.430 Durbin-Watson: 1.639
Prob(Omnibus): 0.807 Jarque-Bera (JB): 0.545
Skew: -0.059 Prob(JB): 0.762
Kurtosis: 2.256 Cond. No. 130.

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: 05:08:06 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: 0.112
Model: OLS Adj. R-squared: 0.070
Method: Least Squares F-statistic: 2.661
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.118
Time: 05:08:06 Log-Likelihood: -111.73
No. Observations: 23 AIC: 227.5
Df Residuals: 21 BIC: 229.7
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 220.2663 86.431 2.548 0.019 40.523 400.010
expression -19.1702 11.752 -1.631 0.118 -43.611 5.270
Omnibus: 3.600 Durbin-Watson: 2.164
Prob(Omnibus): 0.165 Jarque-Bera (JB): 1.799
Skew: 0.381 Prob(JB): 0.407
Kurtosis: 1.861 Cond. No. 95.2

CP101

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

F-statistic p-value df difference
1.215 0.292 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.580
Model: OLS Adj. R-squared: 0.466
Method: Least Squares F-statistic: 5.067
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0191
Time: 05:08:06 Log-Likelihood: -68.791
No. Observations: 15 AIC: 145.6
Df Residuals: 11 BIC: 148.4
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 253.3241 343.871 0.737 0.477 -503.531 1010.179
C(dose)[T.1] -557.0585 417.660 -1.334 0.209 -1476.322 362.205
expression -21.1373 39.082 -0.541 0.599 -107.155 64.881
expression:C(dose)[T.1] 69.0844 47.510 1.454 0.174 -35.485 173.653
Omnibus: 1.457 Durbin-Watson: 0.861
Prob(Omnibus): 0.483 Jarque-Bera (JB): 0.836
Skew: -0.079 Prob(JB): 0.659
Kurtosis: 1.855 Cond. No. 747.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.499
Model: OLS Adj. R-squared: 0.416
Method: Least Squares F-statistic: 5.987
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0157
Time: 05:08:06 Log-Likelihood: -70.110
No. Observations: 15 AIC: 146.2
Df Residuals: 12 BIC: 148.3
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -157.8030 204.609 -0.771 0.455 -603.608 288.002
C(dose)[T.1] 49.9021 15.012 3.324 0.006 17.193 82.611
expression 25.6099 23.232 1.102 0.292 -25.008 76.228
Omnibus: 2.806 Durbin-Watson: 0.968
Prob(Omnibus): 0.246 Jarque-Bera (JB): 2.040
Skew: -0.867 Prob(JB): 0.361
Kurtosis: 2.494 Cond. No. 244.

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: 05:08:06 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: 0.039
Model: OLS Adj. R-squared: -0.035
Method: Least Squares F-statistic: 0.5214
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.483
Time: 05:08:06 Log-Likelihood: -75.005
No. Observations: 15 AIC: 154.0
Df Residuals: 13 BIC: 155.4
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -102.2774 271.540 -0.377 0.713 -688.904 484.349
expression 22.3171 30.906 0.722 0.483 -44.452 89.086
Omnibus: 0.142 Durbin-Watson: 1.838
Prob(Omnibus): 0.931 Jarque-Bera (JB): 0.179
Skew: -0.167 Prob(JB): 0.914
Kurtosis: 2.582 Cond. No. 243.