LID SPN TRAP

1456640_at

Sh3rf2 SH3 domain containing ring finger 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
1.355 0.258 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.697
Model: OLS Adj. R-squared: 0.649
Method: Least Squares F-statistic: 14.54
Date: Thu, 21 Nov 2024 Prob (F-statistic): 3.70e-05
Time: 05:09:31 Log-Likelihood: -99.391
No. Observations: 23 AIC: 206.8
Df Residuals: 19 BIC: 211.3
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 103.3498 176.414 0.586 0.565 -265.888 472.588
C(dose)[T.1] 449.0567 315.428 1.424 0.171 -211.141 1109.254
expression -5.5882 20.050 -0.279 0.783 -47.554 36.378
expression:C(dose)[T.1] -45.1588 35.934 -1.257 0.224 -120.370 30.052
Omnibus: 1.841 Durbin-Watson: 2.082
Prob(Omnibus): 0.398 Jarque-Bera (JB): 1.033
Skew: 0.061 Prob(JB): 0.597
Kurtosis: 1.969 Cond. No. 805.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.671
Model: OLS Adj. R-squared: 0.638
Method: Least Squares F-statistic: 20.43
Date: Thu, 21 Nov 2024 Prob (F-statistic): 1.47e-05
Time: 05:09:31 Log-Likelihood: -100.31
No. Observations: 23 AIC: 206.6
Df Residuals: 20 BIC: 210.0
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 226.9863 148.540 1.528 0.142 -82.862 536.835
C(dose)[T.1] 52.7954 8.500 6.211 0.000 35.065 70.526
expression -19.6477 16.878 -1.164 0.258 -54.855 15.560
Omnibus: 3.318 Durbin-Watson: 1.863
Prob(Omnibus): 0.190 Jarque-Bera (JB): 1.340
Skew: 0.021 Prob(JB): 0.512
Kurtosis: 1.818 Cond. No. 312.

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: 05:09:31 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: 0.037
Model: OLS Adj. R-squared: -0.009
Method: Least Squares F-statistic: 0.8135
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.377
Time: 05:09:31 Log-Likelihood: -112.67
No. Observations: 23 AIC: 229.3
Df Residuals: 21 BIC: 231.6
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 302.6389 247.256 1.224 0.235 -211.558 816.836
expression -25.3879 28.148 -0.902 0.377 -83.924 33.148
Omnibus: 3.245 Durbin-Watson: 2.570
Prob(Omnibus): 0.197 Jarque-Bera (JB): 1.401
Skew: 0.164 Prob(JB): 0.496
Kurtosis: 1.836 Cond. No. 311.

CP101

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

F-statistic p-value df difference
2.266 0.158 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.558
Model: OLS Adj. R-squared: 0.437
Method: Least Squares F-statistic: 4.626
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0251
Time: 05:09:31 Log-Likelihood: -69.180
No. Observations: 15 AIC: 146.4
Df Residuals: 11 BIC: 149.2
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 541.2411 312.678 1.731 0.111 -146.959 1229.441
C(dose)[T.1] -259.0830 405.048 -0.640 0.536 -1150.588 632.422
expression -54.8040 36.145 -1.516 0.158 -134.358 24.750
expression:C(dose)[T.1] 34.8443 47.633 0.732 0.480 -69.994 139.683
Omnibus: 3.744 Durbin-Watson: 1.246
Prob(Omnibus): 0.154 Jarque-Bera (JB): 2.116
Skew: -0.919 Prob(JB): 0.347
Kurtosis: 3.092 Cond. No. 651.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.536
Model: OLS Adj. R-squared: 0.459
Method: Least Squares F-statistic: 6.940
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00994
Time: 05:09:31 Log-Likelihood: -69.536
No. Observations: 15 AIC: 145.1
Df Residuals: 12 BIC: 147.2
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 367.7764 199.822 1.841 0.091 -67.598 803.151
C(dose)[T.1] 36.9611 16.567 2.231 0.046 0.864 73.058
expression -34.7400 23.080 -1.505 0.158 -85.028 15.548
Omnibus: 3.198 Durbin-Watson: 1.013
Prob(Omnibus): 0.202 Jarque-Bera (JB): 1.751
Skew: -0.836 Prob(JB): 0.417
Kurtosis: 3.057 Cond. No. 239.

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: 05:09:31 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: 0.344
Model: OLS Adj. R-squared: 0.294
Method: Least Squares F-statistic: 6.817
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0216
Time: 05:09:31 Log-Likelihood: -72.138
No. Observations: 15 AIC: 148.3
Df Residuals: 13 BIC: 149.7
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 601.1748 194.555 3.090 0.009 180.863 1021.486
expression -60.0051 22.983 -2.611 0.022 -109.656 -10.354
Omnibus: 1.414 Durbin-Watson: 1.847
Prob(Omnibus): 0.493 Jarque-Bera (JB): 0.919
Skew: 0.583 Prob(JB): 0.632
Kurtosis: 2.665 Cond. No. 203.