LID SPN TRAP

1434472_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
0.306 0.586 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.654
Model: OLS Adj. R-squared: 0.600
Method: Least Squares F-statistic: 11.99
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.000124
Time: 04:04:15 Log-Likelihood: -100.89
No. Observations: 23 AIC: 209.8
Df Residuals: 19 BIC: 214.3
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 317.0623 616.529 0.514 0.613 -973.347 1607.472
C(dose)[T.1] 17.8013 919.923 0.019 0.985 -1907.619 1943.221
expression -23.7391 55.678 -0.426 0.675 -140.274 92.796
expression:C(dose)[T.1] 3.2132 83.068 0.039 0.970 -170.651 177.077
Omnibus: 0.374 Durbin-Watson: 1.865
Prob(Omnibus): 0.830 Jarque-Bera (JB): 0.524
Skew: 0.146 Prob(JB): 0.769
Kurtosis: 2.321 Cond. No. 2.92e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.654
Model: OLS Adj. R-squared: 0.620
Method: Least Squares F-statistic: 18.93
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.43e-05
Time: 04:04:15 Log-Likelihood: -100.89
No. Observations: 23 AIC: 207.8
Df Residuals: 20 BIC: 211.2
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 301.0786 445.991 0.675 0.507 -629.242 1231.399
C(dose)[T.1] 53.3834 8.704 6.133 0.000 35.228 71.539
expression -22.2956 40.275 -0.554 0.586 -106.308 61.717
Omnibus: 0.400 Durbin-Watson: 1.865
Prob(Omnibus): 0.819 Jarque-Bera (JB): 0.541
Skew: 0.153 Prob(JB): 0.763
Kurtosis: 2.313 Cond. No. 1.15e+03

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: 04:04:15 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: 0.004
Model: OLS Adj. R-squared: -0.043
Method: Least Squares F-statistic: 0.08919
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.768
Time: 04:04:15 Log-Likelihood: -113.06
No. Observations: 23 AIC: 230.1
Df Residuals: 21 BIC: 232.4
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 300.3341 738.745 0.407 0.688 -1235.970 1836.638
expression -19.9227 66.709 -0.299 0.768 -158.652 118.806
Omnibus: 2.903 Durbin-Watson: 2.435
Prob(Omnibus): 0.234 Jarque-Bera (JB): 1.520
Skew: 0.311 Prob(JB): 0.468
Kurtosis: 1.904 Cond. No. 1.15e+03

CP101

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

F-statistic p-value df difference
4.295 0.060 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.611
Model: OLS Adj. R-squared: 0.504
Method: Least Squares F-statistic: 5.751
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0129
Time: 04:04:15 Log-Likelihood: -68.225
No. Observations: 15 AIC: 144.5
Df Residuals: 11 BIC: 147.3
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -498.3730 1093.821 -0.456 0.658 -2905.858 1909.112
C(dose)[T.1] -826.6706 1295.840 -0.638 0.537 -3678.796 2025.455
expression 49.5197 95.729 0.517 0.615 -161.178 260.217
expression:C(dose)[T.1] 77.8341 113.712 0.684 0.508 -172.445 328.113
Omnibus: 1.003 Durbin-Watson: 0.863
Prob(Omnibus): 0.606 Jarque-Bera (JB): 0.765
Skew: -0.213 Prob(JB): 0.682
Kurtosis: 1.979 Cond. No. 3.14e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.594
Model: OLS Adj. R-squared: 0.526
Method: Least Squares F-statistic: 8.781
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00447
Time: 04:04:15 Log-Likelihood: -68.538
No. Observations: 15 AIC: 143.1
Df Residuals: 12 BIC: 145.2
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -1128.6395 577.188 -1.955 0.074 -2386.224 128.945
C(dose)[T.1] 60.2504 14.522 4.149 0.001 28.610 91.891
expression 104.6815 50.509 2.073 0.060 -5.368 214.731
Omnibus: 2.131 Durbin-Watson: 0.889
Prob(Omnibus): 0.345 Jarque-Bera (JB): 1.024
Skew: -0.180 Prob(JB): 0.599
Kurtosis: 1.771 Cond. No. 983.

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: 04:04:15 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: 0.012
Model: OLS Adj. R-squared: -0.064
Method: Least Squares F-statistic: 0.1549
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.700
Time: 04:04:15 Log-Likelihood: -75.211
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 -221.4265 800.757 -0.277 0.786 -1951.358 1508.505
expression 27.7140 70.425 0.394 0.700 -124.430 179.858
Omnibus: 0.388 Durbin-Watson: 1.718
Prob(Omnibus): 0.823 Jarque-Bera (JB): 0.495
Skew: 0.062 Prob(JB): 0.781
Kurtosis: 2.119 Cond. No. 908.