LID SPN TRAP

1460062_at

Plekhh2 pleckstrin homology domain containing, family H (with MyTH4 domain) member 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
0.336 0.568 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.659
Model: OLS Adj. R-squared: 0.605
Method: Least Squares F-statistic: 12.21
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.000111
Time: 04:39:21 Log-Likelihood: -100.75
No. Observations: 23 AIC: 209.5
Df Residuals: 19 BIC: 214.0
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 55.4597 46.876 1.183 0.251 -42.653 153.572
C(dose)[T.1] 84.8611 65.386 1.298 0.210 -51.993 221.715
expression -0.2664 9.895 -0.027 0.979 -20.977 20.444
expression:C(dose)[T.1] -5.9112 13.049 -0.453 0.656 -33.223 21.400
Omnibus: 0.019 Durbin-Watson: 1.713
Prob(Omnibus): 0.990 Jarque-Bera (JB): 0.158
Skew: -0.058 Prob(JB): 0.924
Kurtosis: 2.610 Cond. No. 104.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.655
Model: OLS Adj. R-squared: 0.620
Method: Least Squares F-statistic: 18.97
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.40e-05
Time: 04:39:21 Log-Likelihood: -100.87
No. Observations: 23 AIC: 207.7
Df Residuals: 20 BIC: 211.1
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 71.4238 30.290 2.358 0.029 8.239 134.608
C(dose)[T.1] 55.5691 9.511 5.843 0.000 35.730 75.408
expression -3.6655 6.321 -0.580 0.568 -16.851 9.520
Omnibus: 0.091 Durbin-Watson: 1.758
Prob(Omnibus): 0.955 Jarque-Bera (JB): 0.294
Skew: -0.094 Prob(JB): 0.863
Kurtosis: 2.479 Cond. No. 36.9

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: 04:39:21 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: 0.066
Model: OLS Adj. R-squared: 0.021
Method: Least Squares F-statistic: 1.478
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.238
Time: 04:39:21 Log-Likelihood: -112.32
No. Observations: 23 AIC: 228.6
Df Residuals: 21 BIC: 230.9
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 23.4488 46.814 0.501 0.622 -73.906 120.804
expression 11.2813 9.281 1.216 0.238 -8.020 30.582
Omnibus: 4.366 Durbin-Watson: 2.607
Prob(Omnibus): 0.113 Jarque-Bera (JB): 2.004
Skew: 0.408 Prob(JB): 0.367
Kurtosis: 1.806 Cond. No. 35.2

CP101

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

F-statistic p-value df difference
3.108 0.103 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.562
Model: OLS Adj. R-squared: 0.443
Method: Least Squares F-statistic: 4.708
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0238
Time: 04:39:21 Log-Likelihood: -69.105
No. Observations: 15 AIC: 146.2
Df Residuals: 11 BIC: 149.0
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -0.1962 51.250 -0.004 0.997 -112.996 112.603
C(dose)[T.1] 53.1512 81.646 0.651 0.528 -126.551 232.853
expression 15.3365 11.367 1.349 0.204 -9.681 40.354
expression:C(dose)[T.1] 0.3568 19.197 0.019 0.986 -41.896 42.609
Omnibus: 4.808 Durbin-Watson: 1.263
Prob(Omnibus): 0.090 Jarque-Bera (JB): 2.355
Skew: -0.917 Prob(JB): 0.308
Kurtosis: 3.636 Cond. No. 62.9

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.562
Model: OLS Adj. R-squared: 0.489
Method: Least Squares F-statistic: 7.704
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00704
Time: 04:39:21 Log-Likelihood: -69.106
No. Observations: 15 AIC: 144.2
Df Residuals: 12 BIC: 146.3
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -0.7478 40.005 -0.019 0.985 -87.911 86.415
C(dose)[T.1] 54.6429 14.364 3.804 0.003 23.347 85.939
expression 15.4616 8.770 1.763 0.103 -3.647 34.570
Omnibus: 4.788 Durbin-Watson: 1.269
Prob(Omnibus): 0.091 Jarque-Bera (JB): 2.349
Skew: -0.918 Prob(JB): 0.309
Kurtosis: 3.625 Cond. No. 26.2

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: 04:39:21 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: 0.034
Model: OLS Adj. R-squared: -0.040
Method: Least Squares F-statistic: 0.4596
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.510
Time: 04:39:21 Log-Likelihood: -75.039
No. Observations: 15 AIC: 154.1
Df Residuals: 13 BIC: 155.5
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 58.6884 52.553 1.117 0.284 -54.846 172.223
expression 8.2857 12.222 0.678 0.510 -18.118 34.690
Omnibus: 1.503 Durbin-Watson: 1.764
Prob(Omnibus): 0.472 Jarque-Bera (JB): 0.887
Skew: 0.181 Prob(JB): 0.642
Kurtosis: 1.865 Cond. No. 23.8