LID SPN TRAP

1460483_at

2610034E01Rik RIKEN cDNA 2610034E01 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
1.482 0.238 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.681
Model: OLS Adj. R-squared: 0.630
Method: Least Squares F-statistic: 13.49
Date: Thu, 21 Nov 2024 Prob (F-statistic): 5.97e-05
Time: 05:19:36 Log-Likelihood: -99.983
No. Observations: 23 AIC: 208.0
Df Residuals: 19 BIC: 212.5
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 15.2597 104.491 0.146 0.885 -203.442 233.962
C(dose)[T.1] -40.1549 145.211 -0.277 0.785 -344.085 263.775
expression 5.4110 14.493 0.373 0.713 -24.923 35.745
expression:C(dose)[T.1] 13.3497 20.330 0.657 0.519 -29.201 55.901
Omnibus: 0.202 Durbin-Watson: 2.118
Prob(Omnibus): 0.904 Jarque-Bera (JB): 0.374
Skew: 0.168 Prob(JB): 0.830
Kurtosis: 2.473 Cond. No. 321.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.673
Model: OLS Adj. R-squared: 0.641
Method: Least Squares F-statistic: 20.61
Date: Thu, 21 Nov 2024 Prob (F-statistic): 1.39e-05
Time: 05:19:36 Log-Likelihood: -100.24
No. Observations: 23 AIC: 206.5
Df Residuals: 20 BIC: 209.9
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -33.5762 72.347 -0.464 0.648 -184.489 117.337
C(dose)[T.1] 55.0271 8.575 6.417 0.000 37.140 72.914
expression 12.1956 10.018 1.217 0.238 -8.702 33.093
Omnibus: 0.191 Durbin-Watson: 2.090
Prob(Omnibus): 0.909 Jarque-Bera (JB): 0.396
Skew: 0.095 Prob(JB): 0.821
Kurtosis: 2.386 Cond. No. 125.

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: 05:19:36 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: 0.001
Model: OLS Adj. R-squared: -0.047
Method: Least Squares F-statistic: 0.01123
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.917
Time: 05:19:36 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 66.9642 120.554 0.555 0.584 -183.742 317.671
expression 1.7882 16.874 0.106 0.917 -33.302 36.879
Omnibus: 3.442 Durbin-Watson: 2.517
Prob(Omnibus): 0.179 Jarque-Bera (JB): 1.584
Skew: 0.281 Prob(JB): 0.453
Kurtosis: 1.844 Cond. No. 122.

CP101

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

F-statistic p-value df difference
0.059 0.813 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.460
Model: OLS Adj. R-squared: 0.312
Method: Least Squares F-statistic: 3.118
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0703
Time: 05:19:36 Log-Likelihood: -70.685
No. Observations: 15 AIC: 149.4
Df Residuals: 11 BIC: 152.2
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -10.4250 176.523 -0.059 0.954 -398.950 378.100
C(dose)[T.1] 157.5054 263.838 0.597 0.563 -423.198 738.209
expression 11.8075 26.711 0.442 0.667 -46.984 70.599
expression:C(dose)[T.1] -16.6333 40.936 -0.406 0.692 -106.734 73.467
Omnibus: 2.756 Durbin-Watson: 0.873
Prob(Omnibus): 0.252 Jarque-Bera (JB): 1.772
Skew: -0.832 Prob(JB): 0.412
Kurtosis: 2.748 Cond. No. 276.

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: 4.938
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0272
Time: 05:19:36 Log-Likelihood: -70.796
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 36.2701 129.245 0.281 0.784 -245.331 317.872
C(dose)[T.1] 50.5317 16.642 3.036 0.010 14.271 86.792
expression 4.7256 19.525 0.242 0.813 -37.815 47.266
Omnibus: 2.149 Durbin-Watson: 0.806
Prob(Omnibus): 0.341 Jarque-Bera (JB): 1.632
Skew: -0.746 Prob(JB): 0.442
Kurtosis: 2.380 Cond. No. 110.

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: 05:19:36 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: 0.030
Model: OLS Adj. R-squared: -0.045
Method: Least Squares F-statistic: 0.4023
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.537
Time: 05:19:36 Log-Likelihood: -75.071
No. Observations: 15 AIC: 154.1
Df Residuals: 13 BIC: 155.6
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 189.8367 151.955 1.249 0.234 -138.443 518.116
expression -14.9267 23.534 -0.634 0.537 -65.769 35.915
Omnibus: 0.231 Durbin-Watson: 1.625
Prob(Omnibus): 0.891 Jarque-Bera (JB): 0.383
Skew: -0.217 Prob(JB): 0.826
Kurtosis: 2.350 Cond. No. 100.