LID SPN TRAP

1434581_at

2410066E13Rik RIKEN cDNA 2410066E13 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
0.498 0.489 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: 0.607
Method: Least Squares F-statistic: 12.31
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.000106
Time: 03:49:57 Log-Likelihood: -100.69
No. Observations: 23 AIC: 209.4
Df Residuals: 19 BIC: 213.9
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -38.5197 120.281 -0.320 0.752 -290.271 213.231
C(dose)[T.1] 124.0378 173.531 0.715 0.483 -239.167 487.242
expression 12.9935 16.832 0.772 0.450 -22.237 48.224
expression:C(dose)[T.1] -9.7188 25.064 -0.388 0.703 -62.178 42.741
Omnibus: 0.439 Durbin-Watson: 1.684
Prob(Omnibus): 0.803 Jarque-Bera (JB): 0.554
Skew: -0.090 Prob(JB): 0.758
Kurtosis: 2.262 Cond. No. 353.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.658
Model: OLS Adj. R-squared: 0.623
Method: Least Squares F-statistic: 19.20
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.22e-05
Time: 03:49:57 Log-Likelihood: -100.78
No. Observations: 23 AIC: 207.6
Df Residuals: 20 BIC: 211.0
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -7.2378 87.299 -0.083 0.935 -189.341 174.865
C(dose)[T.1] 56.8661 10.003 5.685 0.000 36.000 77.732
expression 8.6101 12.204 0.706 0.489 -16.847 34.067
Omnibus: 0.306 Durbin-Watson: 1.743
Prob(Omnibus): 0.858 Jarque-Bera (JB): 0.479
Skew: -0.126 Prob(JB): 0.787
Kurtosis: 2.339 Cond. No. 144.

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: 03:49:57 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: 0.104
Model: OLS Adj. R-squared: 0.062
Method: Least Squares F-statistic: 2.445
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.133
Time: 03:49:57 Log-Likelihood: -111.84
No. Observations: 23 AIC: 227.7
Df Residuals: 21 BIC: 229.9
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 260.7357 115.978 2.248 0.035 19.546 501.925
expression -26.0815 16.681 -1.564 0.133 -60.772 8.609
Omnibus: 0.982 Durbin-Watson: 2.566
Prob(Omnibus): 0.612 Jarque-Bera (JB): 0.877
Skew: 0.250 Prob(JB): 0.645
Kurtosis: 2.185 Cond. No. 120.

CP101

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

F-statistic p-value df difference
0.233 0.638 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: 0.313
Method: Least Squares F-statistic: 3.123
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0700
Time: 03:49:57 Log-Likelihood: -70.679
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 3.9619 353.077 0.011 0.991 -773.155 781.078
C(dose)[T.1] -4.0851 440.714 -0.009 0.993 -974.089 965.919
expression 8.9183 49.586 0.180 0.861 -100.220 118.056
expression:C(dose)[T.1] 7.5753 62.006 0.122 0.905 -128.899 144.050
Omnibus: 3.626 Durbin-Watson: 0.845
Prob(Omnibus): 0.163 Jarque-Bera (JB): 2.138
Skew: -0.925 Prob(JB): 0.343
Kurtosis: 2.996 Cond. No. 556.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.459
Model: OLS Adj. R-squared: 0.369
Method: Least Squares F-statistic: 5.096
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0250
Time: 03:49:57 Log-Likelihood: -70.689
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 -30.5141 203.305 -0.150 0.883 -473.477 412.449
C(dose)[T.1] 49.7203 15.627 3.182 0.008 15.672 83.768
expression 13.7628 28.523 0.483 0.638 -48.384 75.910
Omnibus: 3.588 Durbin-Watson: 0.885
Prob(Omnibus): 0.166 Jarque-Bera (JB): 2.151
Skew: -0.927 Prob(JB): 0.341
Kurtosis: 2.961 Cond. No. 190.

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: 03:49:57 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: 0.003
Model: OLS Adj. R-squared: -0.074
Method: Least Squares F-statistic: 0.04036
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.844
Time: 03:49:57 Log-Likelihood: -75.277
No. Observations: 15 AIC: 154.6
Df Residuals: 13 BIC: 156.0
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 40.7508 263.602 0.155 0.880 -528.727 610.229
expression 7.4570 37.120 0.201 0.844 -72.735 87.649
Omnibus: 0.466 Durbin-Watson: 1.665
Prob(Omnibus): 0.792 Jarque-Bera (JB): 0.526
Skew: 0.024 Prob(JB): 0.769
Kurtosis: 2.084 Cond. No. 188.