LID SPN TRAP

1430565_at

1700030J22Rik RIKEN cDNA 1700030J22 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
3.345 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: Tue, 28 Jan 2025 Prob (F-statistic): 3.28e-05
Time: 19:27:18 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 232.0009 183.770 1.262 0.222 -152.635 616.637
C(dose)[T.1] 122.0007 244.892 0.498 0.624 -390.564 634.566
expression -21.6343 22.351 -0.968 0.345 -68.415 25.146
expression:C(dose)[T.1] -7.7608 29.526 -0.263 0.795 -69.559 54.037
Omnibus: 0.170 Durbin-Watson: 2.393
Prob(Omnibus): 0.918 Jarque-Bera (JB): 0.384
Skew: 0.015 Prob(JB): 0.825
Kurtosis: 2.368 Cond. No. 666.

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: 23.26
Date: Tue, 28 Jan 2025 Prob (F-statistic): 6.04e-06
Time: 19:27:18 Log-Likelihood: -99.284
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 268.5490 117.329 2.289 0.033 23.806 513.292
C(dose)[T.1] 57.6710 8.456 6.820 0.000 40.032 75.310
expression -26.0816 14.261 -1.829 0.082 -55.829 3.665
Omnibus: 0.265 Durbin-Watson: 2.396
Prob(Omnibus): 0.876 Jarque-Bera (JB): 0.449
Skew: 0.010 Prob(JB): 0.799
Kurtosis: 2.316 Cond. No. 244.

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: Tue, 28 Jan 2025 Prob (F-statistic): 3.51e-06
Time: 19:27:18 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: -0.048
Method: Least Squares F-statistic: 0.002316
Date: Tue, 28 Jan 2025 Prob (F-statistic): 0.962
Time: 19:27:18 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 69.9889 202.278 0.346 0.733 -350.671 490.649
expression 1.1725 24.363 0.048 0.962 -49.492 51.837
Omnibus: 3.307 Durbin-Watson: 2.479
Prob(Omnibus): 0.191 Jarque-Bera (JB): 1.572
Skew: 0.291 Prob(JB): 0.456
Kurtosis: 1.859 Cond. No. 236.

CP101

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

F-statistic p-value df difference
0.058 0.814 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.453
Model: OLS Adj. R-squared: 0.303
Method: Least Squares F-statistic: 3.032
Date: Tue, 28 Jan 2025 Prob (F-statistic): 0.0750
Time: 19:27:18 Log-Likelihood: -70.781
No. Observations: 15 AIC: 149.6
Df Residuals: 11 BIC: 152.4
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -27.0685 347.675 -0.078 0.939 -792.296 738.159
C(dose)[T.1] 125.4029 489.270 0.256 0.802 -951.472 1202.278
expression 11.2049 41.201 0.272 0.791 -79.477 101.887
expression:C(dose)[T.1] -8.9996 58.466 -0.154 0.880 -137.683 119.684
Omnibus: 2.359 Durbin-Watson: 0.859
Prob(Omnibus): 0.308 Jarque-Bera (JB): 1.628
Skew: -0.782 Prob(JB): 0.443
Kurtosis: 2.601 Cond. No. 674.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.451
Model: OLS Adj. R-squared: 0.360
Method: Least Squares F-statistic: 4.937
Date: Tue, 28 Jan 2025 Prob (F-statistic): 0.0273
Time: 19:27:19 Log-Likelihood: -70.797
No. Observations: 15 AIC: 147.6
Df Residuals: 12 BIC: 149.7
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 10.6219 236.571 0.045 0.965 -504.823 526.067
C(dose)[T.1] 50.1354 16.180 3.099 0.009 14.881 85.389
expression 6.7358 28.018 0.240 0.814 -54.311 67.782
Omnibus: 2.911 Durbin-Watson: 0.840
Prob(Omnibus): 0.233 Jarque-Bera (JB): 1.902
Skew: -0.862 Prob(JB): 0.386
Kurtosis: 2.732 Cond. No. 257.

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: Tue, 28 Jan 2025 Prob (F-statistic): 0.00629
Time: 19:27:19 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: 0.013
Model: OLS Adj. R-squared: -0.063
Method: Least Squares F-statistic: 0.1646
Date: Tue, 28 Jan 2025 Prob (F-statistic): 0.692
Time: 19:27:19 Log-Likelihood: -75.206
No. Observations: 15 AIC: 154.4
Df Residuals: 13 BIC: 155.8
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 212.5445 293.150 0.725 0.481 -420.768 845.857
expression -14.2211 35.048 -0.406 0.692 -89.938 61.496
Omnibus: 0.062 Durbin-Watson: 1.542
Prob(Omnibus): 0.969 Jarque-Bera (JB): 0.292
Skew: 0.025 Prob(JB): 0.864
Kurtosis: 2.318 Cond. No. 246.