LID SPN TRAP

1460364_at

Gtf2ird1 general transcription factor II I repeat domain-containing 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
0.108 0.746 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.713
Model: OLS Adj. R-squared: 0.668
Method: Least Squares F-statistic: 15.72
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.21e-05
Time: 04:51:35 Log-Likelihood: -98.755
No. Observations: 23 AIC: 205.5
Df Residuals: 19 BIC: 210.1
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 155.9115 63.101 2.471 0.023 23.840 287.983
C(dose)[T.1] -124.8343 87.528 -1.426 0.170 -308.032 58.363
expression -14.6731 9.067 -1.618 0.122 -33.652 4.305
expression:C(dose)[T.1] 27.4034 13.536 2.024 0.057 -0.929 55.736
Omnibus: 0.916 Durbin-Watson: 1.588
Prob(Omnibus): 0.633 Jarque-Bera (JB): 0.784
Skew: -0.146 Prob(JB): 0.676
Kurtosis: 2.144 Cond. No. 183.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.651
Model: OLS Adj. R-squared: 0.616
Method: Least Squares F-statistic: 18.65
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.69e-05
Time: 04:51:35 Log-Likelihood: -101.00
No. Observations: 23 AIC: 208.0
Df Residuals: 20 BIC: 211.4
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 70.6839 50.513 1.399 0.177 -34.684 176.052
C(dose)[T.1] 51.1397 11.011 4.645 0.000 28.172 74.108
expression -2.3770 7.235 -0.329 0.746 -17.469 12.715
Omnibus: 0.161 Durbin-Watson: 1.821
Prob(Omnibus): 0.923 Jarque-Bera (JB): 0.376
Skew: 0.050 Prob(JB): 0.829
Kurtosis: 2.382 Cond. No. 78.2

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: 04:51:35 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: 0.274
Model: OLS Adj. R-squared: 0.240
Method: Least Squares F-statistic: 7.944
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0103
Time: 04:51:35 Log-Likelihood: -109.42
No. Observations: 23 AIC: 222.8
Df Residuals: 21 BIC: 225.1
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 227.6088 52.832 4.308 0.000 117.739 337.478
expression -22.7907 8.086 -2.818 0.010 -39.607 -5.974
Omnibus: 2.211 Durbin-Watson: 1.672
Prob(Omnibus): 0.331 Jarque-Bera (JB): 1.854
Skew: 0.654 Prob(JB): 0.396
Kurtosis: 2.529 Cond. No. 57.5

CP101

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

F-statistic p-value df difference
0.025 0.876 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.509
Model: OLS Adj. R-squared: 0.375
Method: Least Squares F-statistic: 3.801
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0431
Time: 04:51:35 Log-Likelihood: -69.965
No. Observations: 15 AIC: 147.9
Df Residuals: 11 BIC: 150.8
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 225.6680 219.173 1.030 0.325 -256.728 708.064
C(dose)[T.1] -296.8614 301.322 -0.985 0.346 -960.068 366.345
expression -20.0484 27.731 -0.723 0.485 -81.085 40.988
expression:C(dose)[T.1] 44.0092 38.250 1.151 0.274 -40.180 128.198
Omnibus: 5.686 Durbin-Watson: 1.175
Prob(Omnibus): 0.058 Jarque-Bera (JB): 3.115
Skew: -1.081 Prob(JB): 0.211
Kurtosis: 3.555 Cond. No. 419.

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: 4.908
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0277
Time: 04:51:35 Log-Likelihood: -70.817
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 43.0910 153.206 0.281 0.783 -290.716 376.898
C(dose)[T.1] 49.3638 15.758 3.133 0.009 15.030 83.698
expression 3.0835 19.356 0.159 0.876 -39.090 45.257
Omnibus: 2.854 Durbin-Watson: 0.779
Prob(Omnibus): 0.240 Jarque-Bera (JB): 1.929
Skew: -0.862 Prob(JB): 0.381
Kurtosis: 2.665 Cond. No. 157.

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: 04:51:36 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: 0.001469
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.970
Time: 04:51:36 Log-Likelihood: -75.299
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 101.2065 196.995 0.514 0.616 -324.375 526.788
expression -0.9588 25.017 -0.038 0.970 -55.005 53.087
Omnibus: 0.593 Durbin-Watson: 1.622
Prob(Omnibus): 0.744 Jarque-Bera (JB): 0.578
Skew: 0.058 Prob(JB): 0.749
Kurtosis: 2.045 Cond. No. 155.