LID SPN TRAP

1439182_at

D17Wsu92e DNA segment, Chr 17, Wayne State University 92, expressed

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
0.893 0.356 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.708
Model: OLS Adj. R-squared: 0.662
Method: Least Squares F-statistic: 15.33
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.61e-05
Time: 04:31:35 Log-Likelihood: -98.961
No. Observations: 23 AIC: 205.9
Df Residuals: 19 BIC: 210.5
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 290.0690 132.075 2.196 0.041 13.632 566.506
C(dose)[T.1] -335.2425 235.351 -1.424 0.171 -827.838 157.353
expression -30.3760 16.994 -1.787 0.090 -65.945 5.193
expression:C(dose)[T.1] 48.7810 28.973 1.684 0.109 -11.859 109.421
Omnibus: 0.091 Durbin-Watson: 1.700
Prob(Omnibus): 0.955 Jarque-Bera (JB): 0.317
Skew: -0.015 Prob(JB): 0.853
Kurtosis: 2.426 Cond. No. 570.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.664
Model: OLS Adj. R-squared: 0.630
Method: Least Squares F-statistic: 19.77
Date: Thu, 21 Nov 2024 Prob (F-statistic): 1.83e-05
Time: 04:31:35 Log-Likelihood: -100.56
No. Observations: 23 AIC: 207.1
Df Residuals: 20 BIC: 210.5
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 159.7552 111.822 1.429 0.169 -73.502 393.013
C(dose)[T.1] 60.5825 11.506 5.265 0.000 36.582 84.583
expression -13.5932 14.381 -0.945 0.356 -43.592 16.405
Omnibus: 0.096 Durbin-Watson: 1.765
Prob(Omnibus): 0.953 Jarque-Bera (JB): 0.240
Skew: 0.130 Prob(JB): 0.887
Kurtosis: 2.573 Cond. No. 214.

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: 04:31:35 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: 0.198
Model: OLS Adj. R-squared: 0.160
Method: Least Squares F-statistic: 5.197
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0332
Time: 04:31:35 Log-Likelihood: -110.56
No. Observations: 23 AIC: 225.1
Df Residuals: 21 BIC: 227.4
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -215.8524 129.819 -1.663 0.111 -485.827 54.122
expression 36.8558 16.168 2.280 0.033 3.233 70.478
Omnibus: 0.570 Durbin-Watson: 2.420
Prob(Omnibus): 0.752 Jarque-Bera (JB): 0.663
Skew: -0.260 Prob(JB): 0.718
Kurtosis: 2.351 Cond. No. 164.

CP101

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

F-statistic p-value df difference
0.192 0.669 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.467
Model: OLS Adj. R-squared: 0.321
Method: Least Squares F-statistic: 3.207
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0658
Time: 04:31:35 Log-Likelihood: -70.587
No. Observations: 15 AIC: 149.2
Df Residuals: 11 BIC: 152.0
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -156.1724 403.455 -0.387 0.706 -1044.171 731.826
C(dose)[T.1] 238.3132 427.820 0.557 0.589 -703.313 1179.939
expression 28.8605 52.052 0.554 0.590 -85.706 143.427
expression:C(dose)[T.1] -24.0837 55.639 -0.433 0.673 -146.545 98.378
Omnibus: 2.352 Durbin-Watson: 0.923
Prob(Omnibus): 0.309 Jarque-Bera (JB): 1.551
Skew: -0.771 Prob(JB): 0.460
Kurtosis: 2.679 Cond. No. 626.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.457
Model: OLS Adj. R-squared: 0.367
Method: Least Squares F-statistic: 5.059
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0255
Time: 04:31:35 Log-Likelihood: -70.714
No. Observations: 15 AIC: 147.4
Df Residuals: 12 BIC: 149.6
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 7.1352 138.024 0.052 0.960 -293.593 307.863
C(dose)[T.1] 53.3101 18.218 2.926 0.013 13.616 93.005
expression 7.7822 17.754 0.438 0.669 -30.901 46.465
Omnibus: 2.042 Durbin-Watson: 0.878
Prob(Omnibus): 0.360 Jarque-Bera (JB): 1.359
Skew: -0.716 Prob(JB): 0.507
Kurtosis: 2.651 Cond. No. 136.

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: 04:31:35 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: 0.070
Model: OLS Adj. R-squared: -0.001
Method: Least Squares F-statistic: 0.9835
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.339
Time: 04:31:35 Log-Likelihood: -74.753
No. Observations: 15 AIC: 153.5
Df Residuals: 13 BIC: 154.9
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 235.3646 143.215 1.643 0.124 -74.033 544.762
expression -18.9798 19.138 -0.992 0.339 -60.325 22.366
Omnibus: 0.519 Durbin-Watson: 1.519
Prob(Omnibus): 0.771 Jarque-Bera (JB): 0.547
Skew: -0.011 Prob(JB): 0.761
Kurtosis: 2.064 Cond. No. 111.