LID SPN TRAP

1436805_at

Ubash3b ubiquitin associated and SH3 domain containing, B

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
2.566 0.125 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.771
Model: OLS Adj. R-squared: 0.735
Method: Least Squares F-statistic: 21.33
Date: Thu, 03 Apr 2025 Prob (F-statistic): 2.66e-06
Time: 22:47:54 Log-Likelihood: -96.151
No. Observations: 23 AIC: 200.3
Df Residuals: 19 BIC: 204.8
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 111.9942 215.016 0.521 0.608 -338.039 562.028
C(dose)[T.1] 1204.4600 437.774 2.751 0.013 288.188 2120.732
expression -5.2522 19.538 -0.269 0.791 -46.145 35.641
expression:C(dose)[T.1] -101.8711 39.029 -2.610 0.017 -183.561 -20.181
Omnibus: 3.633 Durbin-Watson: 1.844
Prob(Omnibus): 0.163 Jarque-Bera (JB): 2.417
Skew: 0.791 Prob(JB): 0.299
Kurtosis: 3.130 Cond. No. 1.60e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.689
Model: OLS Adj. R-squared: 0.658
Method: Least Squares F-statistic: 22.15
Date: Thu, 03 Apr 2025 Prob (F-statistic): 8.47e-06
Time: 22:47:54 Log-Likelihood: -99.674
No. Observations: 23 AIC: 205.3
Df Residuals: 20 BIC: 208.8
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 392.8549 211.481 1.858 0.078 -48.287 833.997
C(dose)[T.1] 62.0490 9.886 6.276 0.000 41.426 82.672
expression -30.7800 19.215 -1.602 0.125 -70.861 9.301
Omnibus: 3.725 Durbin-Watson: 1.966
Prob(Omnibus): 0.155 Jarque-Bera (JB): 1.415
Skew: 0.040 Prob(JB): 0.493
Kurtosis: 1.787 Cond. No. 577.

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: 22:47:55 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: 0.076
Model: OLS Adj. R-squared: 0.032
Method: Least Squares F-statistic: 1.736
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.202
Time: 22:47:55 Log-Likelihood: -112.19
No. Observations: 23 AIC: 228.4
Df Residuals: 21 BIC: 230.7
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -316.3230 300.626 -1.052 0.305 -941.509 308.863
expression 35.5591 26.985 1.318 0.202 -20.559 91.677
Omnibus: 2.337 Durbin-Watson: 2.252
Prob(Omnibus): 0.311 Jarque-Bera (JB): 1.544
Skew: 0.403 Prob(JB): 0.462
Kurtosis: 2.020 Cond. No. 487.

CP101

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

F-statistic p-value df difference
0.004 0.952 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.485
Model: OLS Adj. R-squared: 0.345
Method: Least Squares F-statistic: 3.458
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.0548
Time: 22:47:55 Log-Likelihood: -70.318
No. Observations: 15 AIC: 148.6
Df Residuals: 11 BIC: 151.5
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 189.5770 202.287 0.937 0.369 -255.654 634.808
C(dose)[T.1] -228.1373 314.406 -0.726 0.483 -920.140 463.865
expression -13.9169 23.010 -0.605 0.558 -64.561 36.727
expression:C(dose)[T.1] 32.1236 36.403 0.882 0.396 -48.000 112.247
Omnibus: 2.121 Durbin-Watson: 1.150
Prob(Omnibus): 0.346 Jarque-Bera (JB): 1.181
Skew: -0.685 Prob(JB): 0.554
Kurtosis: 2.881 Cond. No. 442.

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: Thu, 03 Apr 2025 Prob (F-statistic): 0.0280
Time: 22:47:55 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 76.9347 155.472 0.495 0.630 -261.810 415.679
C(dose)[T.1] 48.9219 16.362 2.990 0.011 13.273 84.571
expression -1.0831 17.665 -0.061 0.952 -39.572 37.406
Omnibus: 2.693 Durbin-Watson: 0.812
Prob(Omnibus): 0.260 Jarque-Bera (JB): 1.874
Skew: -0.842 Prob(JB): 0.392
Kurtosis: 2.597 Cond. No. 174.

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: 22:47:55 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: 0.038
Model: OLS Adj. R-squared: -0.036
Method: Least Squares F-statistic: 0.5191
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.484
Time: 22:47:56 Log-Likelihood: -75.006
No. Observations: 15 AIC: 154.0
Df Residuals: 13 BIC: 155.4
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 227.9320 186.621 1.221 0.244 -175.238 631.102
expression -15.5367 21.564 -0.720 0.484 -62.124 31.050
Omnibus: 2.157 Durbin-Watson: 1.623
Prob(Omnibus): 0.340 Jarque-Bera (JB): 1.007
Skew: 0.137 Prob(JB): 0.604
Kurtosis: 1.761 Cond. No. 164.