LID SPN TRAP

1457351_at

Taf2 TAF2 RNA polymerase II, TATA box binding protein (TBP)-associated factor

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
1.647 0.214 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.678
Model: OLS Adj. R-squared: 0.627
Method: Least Squares F-statistic: 13.32
Date: Thu, 21 Nov 2024 Prob (F-statistic): 6.45e-05
Time: 04:58:45 Log-Likelihood: -100.08
No. Observations: 23 AIC: 208.2
Df Residuals: 19 BIC: 212.7
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 138.4360 69.091 2.004 0.060 -6.173 283.046
C(dose)[T.1] 11.4588 117.520 0.098 0.923 -234.514 257.431
expression -12.3000 10.052 -1.224 0.236 -33.339 8.739
expression:C(dose)[T.1] 6.0369 17.259 0.350 0.730 -30.086 42.160
Omnibus: 0.177 Durbin-Watson: 1.755
Prob(Omnibus): 0.915 Jarque-Bera (JB): 0.389
Skew: -0.051 Prob(JB): 0.823
Kurtosis: 2.371 Cond. No. 230.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.676
Model: OLS Adj. R-squared: 0.643
Method: Least Squares F-statistic: 20.84
Date: Thu, 21 Nov 2024 Prob (F-statistic): 1.28e-05
Time: 04:58:45 Log-Likelihood: -100.15
No. Observations: 23 AIC: 206.3
Df Residuals: 20 BIC: 209.7
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 124.4128 55.022 2.261 0.035 9.640 239.186
C(dose)[T.1] 52.4545 8.458 6.202 0.000 34.812 70.097
expression -10.2522 7.990 -1.283 0.214 -26.918 6.414
Omnibus: 0.077 Durbin-Watson: 1.782
Prob(Omnibus): 0.962 Jarque-Bera (JB): 0.282
Skew: -0.083 Prob(JB): 0.868
Kurtosis: 2.484 Cond. No. 91.3

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: 04:58:45 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: 0.052
Model: OLS Adj. R-squared: 0.007
Method: Least Squares F-statistic: 1.155
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.295
Time: 04:58:45 Log-Likelihood: -112.49
No. Observations: 23 AIC: 229.0
Df Residuals: 21 BIC: 231.2
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 176.9288 90.712 1.950 0.065 -11.717 365.575
expression -14.2819 13.287 -1.075 0.295 -41.914 13.350
Omnibus: 4.398 Durbin-Watson: 2.445
Prob(Omnibus): 0.111 Jarque-Bera (JB): 1.823
Skew: 0.321 Prob(JB): 0.402
Kurtosis: 1.779 Cond. No. 90.0

CP101

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

F-statistic p-value df difference
0.020 0.890 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.563
Model: OLS Adj. R-squared: 0.444
Method: Least Squares F-statistic: 4.721
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0236
Time: 04:58:45 Log-Likelihood: -69.094
No. Observations: 15 AIC: 146.2
Df Residuals: 11 BIC: 149.0
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 627.3479 346.650 1.810 0.098 -135.624 1390.320
C(dose)[T.1] -582.3001 374.304 -1.556 0.148 -1406.138 241.538
expression -76.5295 47.357 -1.616 0.134 -180.763 27.704
expression:C(dose)[T.1] 86.5461 51.295 1.687 0.120 -26.354 199.446
Omnibus: 2.944 Durbin-Watson: 1.272
Prob(Omnibus): 0.229 Jarque-Bera (JB): 1.497
Skew: -0.771 Prob(JB): 0.473
Kurtosis: 3.122 Cond. No. 584.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.450
Model: OLS Adj. R-squared: 0.358
Method: Least Squares F-statistic: 4.903
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0278
Time: 04:58:45 Log-Likelihood: -70.821
No. Observations: 15 AIC: 147.6
Df Residuals: 12 BIC: 149.8
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 87.6319 143.473 0.611 0.553 -224.968 400.232
C(dose)[T.1] 48.7257 16.076 3.031 0.010 13.700 83.752
expression -2.7614 19.547 -0.141 0.890 -45.350 39.828
Omnibus: 2.755 Durbin-Watson: 0.817
Prob(Omnibus): 0.252 Jarque-Bera (JB): 1.885
Skew: -0.849 Prob(JB): 0.390
Kurtosis: 2.635 Cond. No. 135.

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: 04:58:45 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: 0.028
Model: OLS Adj. R-squared: -0.046
Method: Least Squares F-statistic: 0.3796
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.548
Time: 04:58:45 Log-Likelihood: -75.084
No. Observations: 15 AIC: 154.2
Df Residuals: 13 BIC: 155.6
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 202.3487 176.673 1.145 0.273 -179.330 584.028
expression -15.0415 24.412 -0.616 0.548 -67.781 37.698
Omnibus: 1.466 Durbin-Watson: 1.543
Prob(Omnibus): 0.480 Jarque-Bera (JB): 0.887
Skew: 0.198 Prob(JB): 0.642
Kurtosis: 1.877 Cond. No. 130.