LID SPN TRAP

1456769_at

Dusp3 dual specificity phosphatase 3 (vaccinia virus phosphatase VH1-related)

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
0.485 0.494 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.670
Model: OLS Adj. R-squared: 0.617
Method: Least Squares F-statistic: 12.83
Date: Thu, 21 Nov 2024 Prob (F-statistic): 8.17e-05
Time: 03:55:59 Log-Likelihood: -100.37
No. Observations: 23 AIC: 208.7
Df Residuals: 19 BIC: 213.3
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 337.6543 299.201 1.129 0.273 -288.581 963.890
C(dose)[T.1] -634.4499 821.751 -0.772 0.450 -2354.395 1085.495
expression -25.7957 27.224 -0.948 0.355 -82.776 31.185
expression:C(dose)[T.1] 62.6837 74.940 0.836 0.413 -94.167 219.535
Omnibus: 1.006 Durbin-Watson: 2.067
Prob(Omnibus): 0.605 Jarque-Bera (JB): 0.784
Skew: 0.052 Prob(JB): 0.676
Kurtosis: 2.102 Cond. No. 2.38e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.657
Model: OLS Adj. R-squared: 0.623
Method: Least Squares F-statistic: 19.18
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.23e-05
Time: 03:55:59 Log-Likelihood: -100.79
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 246.7557 276.668 0.892 0.383 -330.363 823.874
C(dose)[T.1] 52.8681 8.692 6.083 0.000 34.738 70.999
expression -17.5233 25.173 -0.696 0.494 -70.033 34.987
Omnibus: 0.122 Durbin-Watson: 1.870
Prob(Omnibus): 0.941 Jarque-Bera (JB): 0.344
Skew: -0.039 Prob(JB): 0.842
Kurtosis: 2.406 Cond. No. 708.

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: 03:55:59 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: 0.023
Model: OLS Adj. R-squared: -0.023
Method: Least Squares F-statistic: 0.5054
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.485
Time: 03:55:59 Log-Likelihood: -112.83
No. Observations: 23 AIC: 229.7
Df Residuals: 21 BIC: 231.9
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 402.3170 453.854 0.886 0.385 -541.524 1346.158
expression -29.3933 41.347 -0.711 0.485 -115.380 56.593
Omnibus: 3.072 Durbin-Watson: 2.421
Prob(Omnibus): 0.215 Jarque-Bera (JB): 1.584
Skew: 0.326 Prob(JB): 0.453
Kurtosis: 1.892 Cond. No. 704.

CP101

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

F-statistic p-value df difference
0.005 0.943 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.456
Model: OLS Adj. R-squared: 0.308
Method: Least Squares F-statistic: 3.075
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0726
Time: 03:55:59 Log-Likelihood: -70.732
No. Observations: 15 AIC: 149.5
Df Residuals: 11 BIC: 152.3
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 239.3567 533.251 0.449 0.662 -934.321 1413.035
C(dose)[T.1] -232.0873 742.077 -0.313 0.760 -1865.388 1401.213
expression -16.2606 50.421 -0.322 0.753 -127.237 94.716
expression:C(dose)[T.1] 26.5383 69.954 0.379 0.712 -127.430 180.507
Omnibus: 2.019 Durbin-Watson: 0.922
Prob(Omnibus): 0.364 Jarque-Bera (JB): 1.496
Skew: -0.725 Prob(JB): 0.473
Kurtosis: 2.463 Cond. No. 1.31e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.449
Model: OLS Adj. R-squared: 0.357
Method: Least Squares F-statistic: 4.890
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0280
Time: 03:55:59 Log-Likelihood: -70.830
No. Observations: 15 AIC: 147.7
Df Residuals: 12 BIC: 149.8
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 93.5829 356.302 0.263 0.797 -682.733 869.899
C(dose)[T.1] 49.3617 15.896 3.105 0.009 14.727 83.997
expression -2.4736 33.681 -0.073 0.943 -75.858 70.911
Omnibus: 2.841 Durbin-Watson: 0.829
Prob(Omnibus): 0.242 Jarque-Bera (JB): 1.908
Skew: -0.858 Prob(JB): 0.385
Kurtosis: 2.675 Cond. No. 487.

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: 03:55:59 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: 0.006
Model: OLS Adj. R-squared: -0.070
Method: Least Squares F-statistic: 0.08217
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.779
Time: 03:55:59 Log-Likelihood: -75.253
No. Observations: 15 AIC: 154.5
Df Residuals: 13 BIC: 155.9
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -37.1638 456.507 -0.081 0.936 -1023.388 949.060
expression 12.3321 43.020 0.287 0.779 -80.607 105.271
Omnibus: 0.379 Durbin-Watson: 1.551
Prob(Omnibus): 0.827 Jarque-Bera (JB): 0.489
Skew: 0.040 Prob(JB): 0.783
Kurtosis: 2.119 Cond. No. 482.