LID SPN TRAP

1428466_at

Chd3 chromodomain helicase DNA binding protein 3

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
0.034 0.855 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: 0.606
Method: Least Squares F-statistic: 12.26
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.000108
Time: 22:50:02 Log-Likelihood: -100.72
No. Observations: 23 AIC: 209.4
Df Residuals: 19 BIC: 214.0
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 121.5104 271.665 0.447 0.660 -447.090 690.111
C(dose)[T.1] -317.4278 501.711 -0.633 0.534 -1367.522 732.666
expression -6.7561 27.264 -0.248 0.807 -63.820 50.308
expression:C(dose)[T.1] 37.0533 50.163 0.739 0.469 -67.938 142.045
Omnibus: 0.116 Durbin-Watson: 1.789
Prob(Omnibus): 0.944 Jarque-Bera (JB): 0.323
Skew: 0.098 Prob(JB): 0.851
Kurtosis: 2.453 Cond. No. 1.36e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.650
Model: OLS Adj. R-squared: 0.615
Method: Least Squares F-statistic: 18.54
Date: Thu, 03 Apr 2025 Prob (F-statistic): 2.79e-05
Time: 22:50:02 Log-Likelihood: -101.04
No. Observations: 23 AIC: 208.1
Df Residuals: 20 BIC: 211.5
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 12.4725 225.454 0.055 0.956 -457.817 482.762
C(dose)[T.1] 53.1087 8.849 6.002 0.000 34.651 71.567
expression 4.1896 22.624 0.185 0.855 -43.003 51.382
Omnibus: 0.315 Durbin-Watson: 1.898
Prob(Omnibus): 0.854 Jarque-Bera (JB): 0.481
Skew: 0.058 Prob(JB): 0.786
Kurtosis: 2.301 Cond. No. 520.

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: 22:50:02 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: 0.019
Model: OLS Adj. R-squared: -0.028
Method: Least Squares F-statistic: 0.3991
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.534
Time: 22:50:03 Log-Likelihood: -112.89
No. Observations: 23 AIC: 229.8
Df Residuals: 21 BIC: 232.0
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -151.1530 365.537 -0.414 0.683 -911.328 609.023
expression 23.1153 36.591 0.632 0.534 -52.981 99.211
Omnibus: 2.412 Durbin-Watson: 2.534
Prob(Omnibus): 0.299 Jarque-Bera (JB): 1.274
Skew: 0.211 Prob(JB): 0.529
Kurtosis: 1.927 Cond. No. 516.

CP101

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

F-statistic p-value df difference
0.065 0.804 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.500
Model: OLS Adj. R-squared: 0.364
Method: Least Squares F-statistic: 3.669
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.0472
Time: 22:50:03 Log-Likelihood: -70.099
No. Observations: 15 AIC: 148.2
Df Residuals: 11 BIC: 151.0
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 345.7804 304.378 1.136 0.280 -324.151 1015.712
C(dose)[T.1] -391.8043 427.592 -0.916 0.379 -1332.928 549.319
expression -27.9813 30.576 -0.915 0.380 -95.279 39.316
expression:C(dose)[T.1] 44.2647 42.868 1.033 0.324 -50.088 138.617
Omnibus: 1.426 Durbin-Watson: 0.735
Prob(Omnibus): 0.490 Jarque-Bera (JB): 1.160
Skew: -0.532 Prob(JB): 0.560
Kurtosis: 2.149 Cond. No. 736.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.452
Model: OLS Adj. R-squared: 0.360
Method: Least Squares F-statistic: 4.943
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.0272
Time: 22:50:03 Log-Likelihood: -70.793
No. Observations: 15 AIC: 147.6
Df Residuals: 12 BIC: 149.7
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 121.7668 214.083 0.569 0.580 -344.681 588.215
C(dose)[T.1] 49.4199 15.722 3.143 0.008 15.164 83.675
expression -5.4624 21.490 -0.254 0.804 -52.285 41.360
Omnibus: 2.977 Durbin-Watson: 0.822
Prob(Omnibus): 0.226 Jarque-Bera (JB): 1.903
Skew: -0.865 Prob(JB): 0.386
Kurtosis: 2.777 Cond. No. 276.

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: 22:50:03 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: 0.000
Model: OLS Adj. R-squared: -0.077
Method: Least Squares F-statistic: 0.003666
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.953
Time: 22:50:04 Log-Likelihood: -75.298
No. Observations: 15 AIC: 154.6
Df Residuals: 13 BIC: 156.0
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 110.4706 277.703 0.398 0.697 -489.470 710.411
expression -1.6855 27.836 -0.061 0.953 -61.822 58.451
Omnibus: 0.678 Durbin-Watson: 1.637
Prob(Omnibus): 0.713 Jarque-Bera (JB): 0.609
Skew: 0.059 Prob(JB): 0.737
Kurtosis: 2.020 Cond. No. 275.