LID SPN TRAP

1455085_at

1700086L19Rik RIKEN cDNA 1700086L19 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
1.899 0.183 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: 14.13
Date: Thu, 21 Nov 2024 Prob (F-statistic): 4.44e-05
Time: 05:21:13 Log-Likelihood: -99.617
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 177.9909 280.153 0.635 0.533 -408.377 764.359
C(dose)[T.1] 378.3085 405.228 0.934 0.362 -469.844 1226.461
expression -13.5140 30.579 -0.442 0.664 -77.517 50.489
expression:C(dose)[T.1] -36.9895 44.948 -0.823 0.421 -131.068 57.088
Omnibus: 1.541 Durbin-Watson: 1.994
Prob(Omnibus): 0.463 Jarque-Bera (JB): 1.040
Skew: 0.209 Prob(JB): 0.594
Kurtosis: 2.045 Cond. No. 1.12e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.679
Model: OLS Adj. R-squared: 0.647
Method: Least Squares F-statistic: 21.20
Date: Thu, 21 Nov 2024 Prob (F-statistic): 1.14e-05
Time: 05:21:13 Log-Likelihood: -100.02
No. Observations: 23 AIC: 206.0
Df Residuals: 20 BIC: 209.4
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 334.8018 203.704 1.644 0.116 -90.118 759.722
C(dose)[T.1] 44.9433 10.361 4.338 0.000 23.331 66.555
expression -30.6338 22.230 -1.378 0.183 -77.006 15.738
Omnibus: 0.682 Durbin-Watson: 2.083
Prob(Omnibus): 0.711 Jarque-Bera (JB): 0.672
Skew: 0.105 Prob(JB): 0.714
Kurtosis: 2.189 Cond. No. 446.

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: 05:21:13 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: 0.378
Model: OLS Adj. R-squared: 0.348
Method: Least Squares F-statistic: 12.76
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00180
Time: 05:21:13 Log-Likelihood: -107.65
No. Observations: 23 AIC: 219.3
Df Residuals: 21 BIC: 221.6
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 868.1644 220.809 3.932 0.001 408.966 1327.363
expression -87.3280 24.449 -3.572 0.002 -138.172 -36.484
Omnibus: 0.055 Durbin-Watson: 2.265
Prob(Omnibus): 0.973 Jarque-Bera (JB): 0.200
Skew: -0.099 Prob(JB): 0.905
Kurtosis: 2.588 Cond. No. 355.

CP101

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

F-statistic p-value df difference
2.765 0.122 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.660
Model: OLS Adj. R-squared: 0.568
Method: Least Squares F-statistic: 7.131
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00627
Time: 05:21:13 Log-Likelihood: -67.200
No. Observations: 15 AIC: 142.4
Df Residuals: 11 BIC: 145.2
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 128.8862 246.310 0.523 0.611 -413.240 671.012
C(dose)[T.1] 795.7026 396.041 2.009 0.070 -75.978 1667.384
expression -7.4606 29.879 -0.250 0.807 -73.223 58.302
expression:C(dose)[T.1] -89.3095 47.658 -1.874 0.088 -194.205 15.586
Omnibus: 0.354 Durbin-Watson: 1.270
Prob(Omnibus): 0.838 Jarque-Bera (JB): 0.286
Skew: -0.277 Prob(JB): 0.867
Kurtosis: 2.610 Cond. No. 658.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.552
Model: OLS Adj. R-squared: 0.477
Method: Least Squares F-statistic: 7.393
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00809
Time: 05:21:13 Log-Likelihood: -69.278
No. Observations: 15 AIC: 144.6
Df Residuals: 12 BIC: 146.7
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 418.0518 211.122 1.980 0.071 -41.944 878.048
C(dose)[T.1] 53.9492 14.475 3.727 0.003 22.412 85.487
expression -42.5635 25.598 -1.663 0.122 -98.337 13.210
Omnibus: 0.673 Durbin-Watson: 1.204
Prob(Omnibus): 0.714 Jarque-Bera (JB): 0.612
Skew: -0.086 Prob(JB): 0.737
Kurtosis: 2.026 Cond. No. 252.

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: 05:21:13 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: 0.033
Model: OLS Adj. R-squared: -0.041
Method: Least Squares F-statistic: 0.4487
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.515
Time: 05:21:13 Log-Likelihood: -75.046
No. Observations: 15 AIC: 154.1
Df Residuals: 13 BIC: 155.5
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 290.5004 294.009 0.988 0.341 -344.667 925.667
expression -23.7229 35.414 -0.670 0.515 -100.231 52.785
Omnibus: 0.599 Durbin-Watson: 1.817
Prob(Omnibus): 0.741 Jarque-Bera (JB): 0.582
Skew: 0.066 Prob(JB): 0.748
Kurtosis: 2.044 Cond. No. 248.