LID SPN TRAP

1457473_at

Chd1 chromodomain helicase DNA binding protein 1

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
0.062 0.806 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.651
Model: OLS Adj. R-squared: 0.595
Method: Least Squares F-statistic: 11.79
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.000137
Time: 22:54:32 Log-Likelihood: -101.01
No. Observations: 23 AIC: 210.0
Df Residuals: 19 BIC: 214.6
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 40.1825 49.578 0.810 0.428 -63.586 143.951
C(dose)[T.1] 66.0498 85.662 0.771 0.450 -113.243 245.343
expression 2.2713 7.965 0.285 0.779 -14.401 18.943
expression:C(dose)[T.1] -2.0632 13.604 -0.152 0.881 -30.536 26.410
Omnibus: 0.185 Durbin-Watson: 1.816
Prob(Omnibus): 0.911 Jarque-Bera (JB): 0.395
Skew: 0.052 Prob(JB): 0.821
Kurtosis: 2.367 Cond. No. 149.

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: 18.58
Date: Thu, 03 Apr 2025 Prob (F-statistic): 2.75e-05
Time: 22:54:32 Log-Likelihood: -101.03
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 44.5506 39.356 1.132 0.271 -37.545 126.646
C(dose)[T.1] 53.1303 8.796 6.040 0.000 34.782 71.478
expression 1.5640 6.297 0.248 0.806 -11.572 14.700
Omnibus: 0.216 Durbin-Watson: 1.849
Prob(Omnibus): 0.898 Jarque-Bera (JB): 0.417
Skew: 0.059 Prob(JB): 0.812
Kurtosis: 2.351 Cond. No. 58.1

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: 22:54:32 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: 0.012
Model: OLS Adj. R-squared: -0.035
Method: Least Squares F-statistic: 0.2524
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.621
Time: 22:54:32 Log-Likelihood: -112.97
No. Observations: 23 AIC: 229.9
Df Residuals: 21 BIC: 232.2
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 47.4955 64.542 0.736 0.470 -86.727 181.718
expression 5.1651 10.282 0.502 0.621 -16.217 26.547
Omnibus: 2.780 Durbin-Watson: 2.360
Prob(Omnibus): 0.249 Jarque-Bera (JB): 1.473
Skew: 0.299 Prob(JB): 0.479
Kurtosis: 1.913 Cond. No. 57.9

CP101

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

F-statistic p-value df difference
2.467 0.142 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.571
Model: OLS Adj. R-squared: 0.454
Method: Least Squares F-statistic: 4.877
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.0215
Time: 22:54:32 Log-Likelihood: -68.956
No. Observations: 15 AIC: 145.9
Df Residuals: 11 BIC: 148.7
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 268.4531 114.189 2.351 0.038 17.126 519.780
C(dose)[T.1] -162.5945 255.300 -0.637 0.537 -724.506 399.317
expression -30.5159 17.259 -1.768 0.105 -68.503 7.472
expression:C(dose)[T.1] 32.1064 37.863 0.848 0.415 -51.229 115.442
Omnibus: 3.832 Durbin-Watson: 1.136
Prob(Omnibus): 0.147 Jarque-Bera (JB): 1.939
Skew: -0.867 Prob(JB): 0.379
Kurtosis: 3.310 Cond. No. 289.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.543
Model: OLS Adj. R-squared: 0.467
Method: Least Squares F-statistic: 7.123
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.00914
Time: 22:54:32 Log-Likelihood: -69.431
No. Observations: 15 AIC: 144.9
Df Residuals: 12 BIC: 147.0
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 224.5058 100.552 2.233 0.045 5.423 443.589
C(dose)[T.1] 53.5282 14.598 3.667 0.003 21.722 85.334
expression -23.8446 15.181 -1.571 0.142 -56.921 9.232
Omnibus: 11.346 Durbin-Watson: 0.834
Prob(Omnibus): 0.003 Jarque-Bera (JB): 7.513
Skew: -1.398 Prob(JB): 0.0234
Kurtosis: 5.051 Cond. No. 96.7

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: 22:54:32 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: 0.030
Model: OLS Adj. R-squared: -0.044
Method: Least Squares F-statistic: 0.4084
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.534
Time: 22:54:32 Log-Likelihood: -75.068
No. Observations: 15 AIC: 154.1
Df Residuals: 13 BIC: 155.6
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 182.7558 139.773 1.308 0.214 -119.206 484.718
expression -13.3279 20.857 -0.639 0.534 -58.386 31.730
Omnibus: 2.665 Durbin-Watson: 1.770
Prob(Omnibus): 0.264 Jarque-Bera (JB): 1.177
Skew: 0.249 Prob(JB): 0.555
Kurtosis: 1.721 Cond. No. 95.7