LID SPN TRAP

1448684_at

Ppp1r2 protein phosphatase 1, regulatory (inhibitor) subunit 2

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
1.583 0.223 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.675
Model: OLS Adj. R-squared: 0.624
Method: Least Squares F-statistic: 13.15
Date: Fri, 31 Oct 2025 Prob (F-statistic): 7.01e-05
Time: 12:37:52 Log-Likelihood: -100.18
No. Observations: 23 AIC: 208.4
Df Residuals: 19 BIC: 212.9
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -426.5286 507.540 -0.840 0.411 -1488.822 635.765
C(dose)[T.1] -30.5006 880.557 -0.035 0.973 -1873.527 1812.526
expression 40.5342 42.791 0.947 0.355 -49.029 130.097
expression:C(dose)[T.1] 6.6016 73.756 0.090 0.930 -147.772 160.975
Omnibus: 1.371 Durbin-Watson: 1.887
Prob(Omnibus): 0.504 Jarque-Bera (JB): 0.925
Skew: 0.118 Prob(JB): 0.630
Kurtosis: 2.046 Cond. No. 2.96e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.675
Model: OLS Adj. R-squared: 0.642
Method: Least Squares F-statistic: 20.75
Date: Fri, 31 Oct 2025 Prob (F-statistic): 1.32e-05
Time: 12:37:52 Log-Likelihood: -100.19
No. Observations: 23 AIC: 206.4
Df Residuals: 20 BIC: 209.8
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -452.8826 403.021 -1.124 0.274 -1293.569 387.804
C(dose)[T.1] 48.3098 9.340 5.173 0.000 28.828 67.792
expression 42.7563 33.978 1.258 0.223 -28.120 113.633
Omnibus: 1.371 Durbin-Watson: 1.870
Prob(Omnibus): 0.504 Jarque-Bera (JB): 0.920
Skew: 0.108 Prob(JB): 0.631
Kurtosis: 2.044 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: Fri, 31 Oct 2025 Prob (F-statistic): 3.51e-06
Time: 12:37:52 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: 0.240
Model: OLS Adj. R-squared: 0.204
Method: Least Squares F-statistic: 6.623
Date: Fri, 31 Oct 2025 Prob (F-statistic): 0.0177
Time: 12:37:52 Log-Likelihood: -109.95
No. Observations: 23 AIC: 223.9
Df Residuals: 21 BIC: 226.2
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -1325.6498 546.117 -2.427 0.024 -2461.363 -189.937
expression 117.9370 45.827 2.574 0.018 22.635 213.239
Omnibus: 1.972 Durbin-Watson: 2.338
Prob(Omnibus): 0.373 Jarque-Bera (JB): 1.275
Skew: 0.303 Prob(JB): 0.529
Kurtosis: 2.018 Cond. No. 1.04e+03

CP101

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

F-statistic p-value df difference
0.003 0.956 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.482
Model: OLS Adj. R-squared: 0.340
Method: Least Squares F-statistic: 3.406
Date: Fri, 31 Oct 2025 Prob (F-statistic): 0.0569
Time: 12:37:52 Log-Likelihood: -70.373
No. Observations: 15 AIC: 148.7
Df Residuals: 11 BIC: 151.6
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -979.5827 1535.402 -0.638 0.537 -4358.979 2399.814
C(dose)[T.1] 1706.8321 1992.352 0.857 0.410 -2678.306 6091.970
expression 89.7705 131.641 0.682 0.509 -199.970 379.511
expression:C(dose)[T.1] -141.0504 169.403 -0.833 0.423 -513.904 231.803
Omnibus: 3.502 Durbin-Watson: 0.993
Prob(Omnibus): 0.174 Jarque-Bera (JB): 2.072
Skew: -0.910 Prob(JB): 0.355
Kurtosis: 2.974 Cond. No. 4.14e+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: 4.888
Date: Fri, 31 Oct 2025 Prob (F-statistic): 0.0280
Time: 12:37:52 Log-Likelihood: -70.831
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 13.8399 953.978 0.015 0.989 -2064.701 2092.380
C(dose)[T.1] 48.0731 25.446 1.889 0.083 -7.368 103.514
expression 4.5947 81.788 0.056 0.956 -173.606 182.795
Omnibus: 2.668 Durbin-Watson: 0.824
Prob(Omnibus): 0.263 Jarque-Bera (JB): 1.861
Skew: -0.838 Prob(JB): 0.394
Kurtosis: 2.590 Cond. No. 1.45e+03

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: Fri, 31 Oct 2025 Prob (F-statistic): 0.00629
Time: 12:37:52 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: 0.285
Model: OLS Adj. R-squared: 0.230
Method: Least Squares F-statistic: 5.182
Date: Fri, 31 Oct 2025 Prob (F-statistic): 0.0404
Time: 12:37:52 Log-Likelihood: -72.784
No. Observations: 15 AIC: 149.6
Df Residuals: 13 BIC: 151.0
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -1392.5024 652.919 -2.133 0.053 -2803.048 18.043
expression 126.0150 55.357 2.276 0.040 6.423 245.607
Omnibus: 1.329 Durbin-Watson: 1.475
Prob(Omnibus): 0.515 Jarque-Bera (JB): 0.796
Skew: 0.032 Prob(JB): 0.672
Kurtosis: 1.873 Cond. No. 903.