LID SPN TRAP

1454884_at

Zbtb46 zinc finger and BTB domain containing 46

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
1.744 0.202 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.677
Model: OLS Adj. R-squared: 0.626
Method: Least Squares F-statistic: 13.29
Date: Thu, 21 Nov 2024 Prob (F-statistic): 6.56e-05
Time: 04:10:57 Log-Likelihood: -100.10
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 105.2375 45.454 2.315 0.032 10.100 200.375
C(dose)[T.1] 55.3867 97.775 0.566 0.578 -149.258 260.031
expression -12.9898 11.471 -1.132 0.272 -36.998 11.018
expression:C(dose)[T.1] -1.5942 26.351 -0.060 0.952 -56.747 53.559
Omnibus: 1.274 Durbin-Watson: 1.801
Prob(Omnibus): 0.529 Jarque-Bera (JB): 0.867
Skew: -0.026 Prob(JB): 0.648
Kurtosis: 2.050 Cond. No. 106.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.677
Model: OLS Adj. R-squared: 0.645
Method: Least Squares F-statistic: 20.98
Date: Thu, 21 Nov 2024 Prob (F-statistic): 1.23e-05
Time: 04:10:57 Log-Likelihood: -100.10
No. Observations: 23 AIC: 206.2
Df Residuals: 20 BIC: 209.6
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 106.4242 39.970 2.663 0.015 23.048 189.800
C(dose)[T.1] 49.4974 8.899 5.562 0.000 30.934 68.061
expression -13.2919 10.066 -1.320 0.202 -34.290 7.706
Omnibus: 1.191 Durbin-Watson: 1.810
Prob(Omnibus): 0.551 Jarque-Bera (JB): 0.842
Skew: -0.035 Prob(JB): 0.656
Kurtosis: 2.065 Cond. No. 39.1

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, 21 Nov 2024 Prob (F-statistic): 3.51e-06
Time: 04:10:57 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: 0.178
Model: OLS Adj. R-squared: 0.139
Method: Least Squares F-statistic: 4.545
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0450
Time: 04:10:57 Log-Likelihood: -110.85
No. Observations: 23 AIC: 225.7
Df Residuals: 21 BIC: 228.0
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 199.4363 56.538 3.527 0.002 81.858 317.015
expression -31.5860 14.817 -2.132 0.045 -62.399 -0.773
Omnibus: 0.421 Durbin-Watson: 2.316
Prob(Omnibus): 0.810 Jarque-Bera (JB): 0.556
Skew: 0.168 Prob(JB): 0.757
Kurtosis: 2.316 Cond. No. 35.2

CP101

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

F-statistic p-value df difference
7.529 0.018 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.682
Model: OLS Adj. R-squared: 0.595
Method: Least Squares F-statistic: 7.869
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00441
Time: 04:10:58 Log-Likelihood: -66.704
No. Observations: 15 AIC: 141.4
Df Residuals: 11 BIC: 144.2
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 170.1222 112.074 1.518 0.157 -76.551 416.795
C(dose)[T.1] 155.9029 136.736 1.140 0.278 -145.051 456.857
expression -18.2811 19.885 -0.919 0.378 -62.047 25.485
expression:C(dose)[T.1] -20.9556 24.664 -0.850 0.414 -75.240 33.329
Omnibus: 0.208 Durbin-Watson: 1.789
Prob(Omnibus): 0.901 Jarque-Bera (JB): 0.285
Skew: 0.224 Prob(JB): 0.867
Kurtosis: 2.496 Cond. No. 177.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.661
Model: OLS Adj. R-squared: 0.605
Method: Least Squares F-statistic: 11.71
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00151
Time: 04:10:58 Log-Likelihood: -67.180
No. Observations: 15 AIC: 140.4
Df Residuals: 12 BIC: 142.5
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 246.6410 65.930 3.741 0.003 102.991 390.291
C(dose)[T.1] 40.2438 12.762 3.153 0.008 12.438 68.050
expression -31.9028 11.627 -2.744 0.018 -57.235 -6.571
Omnibus: 0.553 Durbin-Watson: 1.867
Prob(Omnibus): 0.759 Jarque-Bera (JB): 0.601
Skew: 0.341 Prob(JB): 0.740
Kurtosis: 2.294 Cond. No. 61.1

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: 04:10:58 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: 0.381
Model: OLS Adj. R-squared: 0.333
Method: Least Squares F-statistic: 7.989
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0143
Time: 04:10:58 Log-Likelihood: -71.707
No. Observations: 15 AIC: 147.4
Df Residuals: 13 BIC: 148.8
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 319.3547 80.249 3.980 0.002 145.988 492.721
expression -41.2759 14.604 -2.826 0.014 -72.825 -9.727
Omnibus: 0.395 Durbin-Watson: 2.003
Prob(Omnibus): 0.821 Jarque-Bera (JB): 0.271
Skew: 0.281 Prob(JB): 0.873
Kurtosis: 2.656 Cond. No. 57.0