LID SPN TRAP

1438578_a_at

Btbd10 BTB (POZ) domain containing 10

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
0.058 0.812 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.661
Model: OLS Adj. R-squared: 0.608
Method: Least Squares F-statistic: 12.37
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.000103
Time: 03:55:59 Log-Likelihood: -100.65
No. Observations: 23 AIC: 209.3
Df Residuals: 19 BIC: 213.8
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 350.6319 418.822 0.837 0.413 -525.972 1227.235
C(dose)[T.1] -443.9435 625.284 -0.710 0.486 -1752.679 864.792
expression -29.6824 41.934 -0.708 0.488 -117.452 58.087
expression:C(dose)[T.1] 49.9329 62.843 0.795 0.437 -81.600 181.466
Omnibus: 0.777 Durbin-Watson: 2.080
Prob(Omnibus): 0.678 Jarque-Bera (JB): 0.747
Skew: 0.185 Prob(JB): 0.688
Kurtosis: 2.199 Cond. No. 1.80e+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: 18.58
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.75e-05
Time: 03:55:59 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 128.5978 309.078 0.416 0.682 -516.129 773.324
C(dose)[T.1] 52.8311 9.006 5.866 0.000 34.045 71.617
expression -7.4490 30.944 -0.241 0.812 -71.996 57.098
Omnibus: 0.145 Durbin-Watson: 1.900
Prob(Omnibus): 0.930 Jarque-Bera (JB): 0.364
Skew: 0.024 Prob(JB): 0.834
Kurtosis: 2.386 Cond. No. 711.

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: 03:55:59 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: 0.048
Model: OLS Adj. R-squared: 0.003
Method: Least Squares F-statistic: 1.058
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.315
Time: 03:55:59 Log-Likelihood: -112.54
No. Observations: 23 AIC: 229.1
Df Residuals: 21 BIC: 231.4
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 575.5770 482.167 1.194 0.246 -427.144 1578.298
expression -49.8150 48.434 -1.029 0.315 -150.539 50.909
Omnibus: 4.530 Durbin-Watson: 2.427
Prob(Omnibus): 0.104 Jarque-Bera (JB): 1.840
Skew: 0.318 Prob(JB): 0.399
Kurtosis: 1.769 Cond. No. 689.

CP101

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

F-statistic p-value df difference
0.075 0.789 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.558
Model: OLS Adj. R-squared: 0.437
Method: Least Squares F-statistic: 4.627
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0251
Time: 03:55:59 Log-Likelihood: -69.179
No. Observations: 15 AIC: 146.4
Df Residuals: 11 BIC: 149.2
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -473.4029 576.047 -0.822 0.429 -1741.273 794.467
C(dose)[T.1] 1360.7818 810.002 1.680 0.121 -422.021 3143.585
expression 55.8117 59.435 0.939 0.368 -75.005 186.628
expression:C(dose)[T.1] -136.4232 84.134 -1.621 0.133 -321.601 48.755
Omnibus: 1.076 Durbin-Watson: 1.192
Prob(Omnibus): 0.584 Jarque-Bera (JB): 0.837
Skew: -0.520 Prob(JB): 0.658
Kurtosis: 2.492 Cond. No. 1.42e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.452
Model: OLS Adj. R-squared: 0.361
Method: Least Squares F-statistic: 4.953
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0270
Time: 03:55:59 Log-Likelihood: -70.786
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 186.3328 434.585 0.429 0.676 -760.547 1133.213
C(dose)[T.1] 47.6141 16.722 2.847 0.015 11.180 84.048
expression -12.2704 44.832 -0.274 0.789 -109.951 85.410
Omnibus: 2.312 Durbin-Watson: 0.826
Prob(Omnibus): 0.315 Jarque-Bera (JB): 1.670
Skew: -0.780 Prob(JB): 0.434
Kurtosis: 2.510 Cond. No. 541.

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: 03:55:59 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: 0.082
Model: OLS Adj. R-squared: 0.011
Method: Least Squares F-statistic: 1.162
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.301
Time: 03:55:59 Log-Likelihood: -74.658
No. Observations: 15 AIC: 153.3
Df Residuals: 13 BIC: 154.7
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 636.3639 503.476 1.264 0.228 -451.331 1724.059
expression -56.4045 52.318 -1.078 0.301 -169.432 56.622
Omnibus: 0.483 Durbin-Watson: 1.519
Prob(Omnibus): 0.786 Jarque-Bera (JB): 0.547
Skew: -0.135 Prob(JB): 0.761
Kurtosis: 2.105 Cond. No. 503.