LID SPN TRAP

1417342_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
3.068 0.095 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.696
Model: OLS Adj. R-squared: 0.648
Method: Least Squares F-statistic: 14.49
Date: Thu, 03 Apr 2025 Prob (F-statistic): 3.78e-05
Time: 22:46:39 Log-Likelihood: -99.418
No. Observations: 23 AIC: 206.8
Df Residuals: 19 BIC: 211.4
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -353.3269 278.715 -1.268 0.220 -936.684 230.030
C(dose)[T.1] 79.6040 513.418 0.155 0.878 -994.993 1154.201
expression 42.0715 28.767 1.463 0.160 -18.138 102.281
expression:C(dose)[T.1] -3.9228 51.850 -0.076 0.940 -112.447 104.601
Omnibus: 0.430 Durbin-Watson: 1.542
Prob(Omnibus): 0.806 Jarque-Bera (JB): 0.548
Skew: 0.083 Prob(JB): 0.760
Kurtosis: 2.262 Cond. No. 1.46e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.696
Model: OLS Adj. R-squared: 0.665
Method: Least Squares F-statistic: 22.87
Date: Thu, 03 Apr 2025 Prob (F-statistic): 6.80e-06
Time: 22:46:39 Log-Likelihood: -99.422
No. Observations: 23 AIC: 204.8
Df Residuals: 20 BIC: 208.2
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -341.6306 226.070 -1.511 0.146 -813.205 129.944
C(dose)[T.1] 40.7700 10.870 3.751 0.001 18.095 63.445
expression 40.8641 23.331 1.752 0.095 -7.803 89.531
Omnibus: 0.398 Durbin-Watson: 1.553
Prob(Omnibus): 0.820 Jarque-Bera (JB): 0.532
Skew: 0.093 Prob(JB): 0.767
Kurtosis: 2.279 Cond. No. 552.

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, 03 Apr 2025 Prob (F-statistic): 3.51e-06
Time: 22:46:39 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: 0.482
Model: OLS Adj. R-squared: 0.457
Method: Least Squares F-statistic: 19.52
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.000239
Time: 22:46:39 Log-Likelihood: -105.55
No. Observations: 23 AIC: 215.1
Df Residuals: 21 BIC: 217.4
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -890.1154 219.581 -4.054 0.001 -1346.759 -433.472
expression 98.6223 22.323 4.418 0.000 52.199 145.045
Omnibus: 1.760 Durbin-Watson: 1.886
Prob(Omnibus): 0.415 Jarque-Bera (JB): 1.515
Skew: 0.574 Prob(JB): 0.469
Kurtosis: 2.489 Cond. No. 420.

CP101

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

F-statistic p-value df difference
0.431 0.524 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.515
Model: OLS Adj. R-squared: 0.383
Method: Least Squares F-statistic: 3.901
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.0402
Time: 22:46:39 Log-Likelihood: -69.865
No. Observations: 15 AIC: 147.7
Df Residuals: 11 BIC: 150.6
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -203.0751 251.485 -0.808 0.436 -756.590 350.440
C(dose)[T.1] 603.9604 539.232 1.120 0.287 -582.881 1790.802
expression 29.8667 27.739 1.077 0.305 -31.186 90.920
expression:C(dose)[T.1] -60.1105 57.825 -1.040 0.321 -187.383 67.162
Omnibus: 5.582 Durbin-Watson: 0.653
Prob(Omnibus): 0.061 Jarque-Bera (JB): 2.906
Skew: -1.022 Prob(JB): 0.234
Kurtosis: 3.688 Cond. No. 789.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.468
Model: OLS Adj. R-squared: 0.379
Method: Least Squares F-statistic: 5.276
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.0227
Time: 22:46:39 Log-Likelihood: -70.568
No. Observations: 15 AIC: 147.1
Df Residuals: 12 BIC: 149.3
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -77.7949 221.467 -0.351 0.731 -560.329 404.740
C(dose)[T.1] 43.7139 17.575 2.487 0.029 5.422 82.006
expression 16.0343 24.421 0.657 0.524 -37.174 69.242
Omnibus: 1.743 Durbin-Watson: 0.753
Prob(Omnibus): 0.418 Jarque-Bera (JB): 1.384
Skew: -0.629 Prob(JB): 0.501
Kurtosis: 2.204 Cond. No. 269.

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, 03 Apr 2025 Prob (F-statistic): 0.00629
Time: 22:46:39 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: 0.194
Model: OLS Adj. R-squared: 0.132
Method: Least Squares F-statistic: 3.120
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.101
Time: 22:46:39 Log-Likelihood: -73.687
No. Observations: 15 AIC: 151.4
Df Residuals: 13 BIC: 152.8
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -321.1274 235.006 -1.366 0.195 -828.826 186.572
expression 44.8941 25.416 1.766 0.101 -10.014 99.802
Omnibus: 3.513 Durbin-Watson: 1.274
Prob(Omnibus): 0.173 Jarque-Bera (JB): 1.417
Skew: 0.339 Prob(JB): 0.492
Kurtosis: 1.656 Cond. No. 241.