LID SPN TRAP

1428221_at

Klhdc8b kelch domain containing 8B

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
2.898 0.104 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.699
Model: OLS Adj. R-squared: 0.652
Method: Least Squares F-statistic: 14.71
Date: Thu, 21 Nov 2024 Prob (F-statistic): 3.42e-05
Time: 05:02:49 Log-Likelihood: -99.294
No. Observations: 23 AIC: 206.6
Df Residuals: 19 BIC: 211.1
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -4.6750 81.394 -0.057 0.955 -175.035 165.685
C(dose)[T.1] -17.2193 114.120 -0.151 0.882 -256.074 221.636
expression 11.4201 15.746 0.725 0.477 -21.538 44.378
expression:C(dose)[T.1] 12.9656 21.766 0.596 0.558 -32.591 58.522
Omnibus: 1.607 Durbin-Watson: 2.171
Prob(Omnibus): 0.448 Jarque-Bera (JB): 1.426
Skew: 0.522 Prob(JB): 0.490
Kurtosis: 2.370 Cond. No. 195.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.693
Model: OLS Adj. R-squared: 0.663
Method: Least Squares F-statistic: 22.62
Date: Thu, 21 Nov 2024 Prob (F-statistic): 7.32e-06
Time: 05:02:49 Log-Likelihood: -99.506
No. Observations: 23 AIC: 205.0
Df Residuals: 20 BIC: 208.4
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -39.6635 55.431 -0.716 0.483 -155.291 75.964
C(dose)[T.1] 50.5713 8.356 6.052 0.000 33.142 68.001
expression 18.2060 10.694 1.702 0.104 -4.102 40.514
Omnibus: 1.730 Durbin-Watson: 2.205
Prob(Omnibus): 0.421 Jarque-Bera (JB): 1.435
Skew: 0.463 Prob(JB): 0.488
Kurtosis: 2.199 Cond. No. 73.9

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: 05:02:49 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: 0.132
Model: OLS Adj. R-squared: 0.091
Method: Least Squares F-statistic: 3.195
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0883
Time: 05:02:49 Log-Likelihood: -111.48
No. Observations: 23 AIC: 227.0
Df Residuals: 21 BIC: 229.2
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -81.2827 90.325 -0.900 0.378 -269.123 106.558
expression 30.7913 17.227 1.787 0.088 -5.034 66.616
Omnibus: 1.606 Durbin-Watson: 2.993
Prob(Omnibus): 0.448 Jarque-Bera (JB): 1.129
Skew: 0.275 Prob(JB): 0.569
Kurtosis: 2.064 Cond. No. 73.0

CP101

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

F-statistic p-value df difference
0.835 0.379 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.541
Model: OLS Adj. R-squared: 0.416
Method: Least Squares F-statistic: 4.330
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0303
Time: 05:02:49 Log-Likelihood: -69.452
No. Observations: 15 AIC: 146.9
Df Residuals: 11 BIC: 149.7
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 133.7976 169.814 0.788 0.447 -239.961 507.556
C(dose)[T.1] -187.4429 207.220 -0.905 0.385 -643.531 268.645
expression -11.3652 29.019 -0.392 0.703 -75.236 52.505
expression:C(dose)[T.1] 42.0577 36.013 1.168 0.268 -37.207 121.322
Omnibus: 0.854 Durbin-Watson: 1.183
Prob(Omnibus): 0.652 Jarque-Bera (JB): 0.790
Skew: -0.441 Prob(JB): 0.674
Kurtosis: 2.302 Cond. No. 231.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.485
Model: OLS Adj. R-squared: 0.399
Method: Least Squares F-statistic: 5.642
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0187
Time: 05:02:49 Log-Likelihood: -70.328
No. Observations: 15 AIC: 146.7
Df Residuals: 12 BIC: 148.8
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -25.6714 102.470 -0.251 0.806 -248.934 197.591
C(dose)[T.1] 53.8522 16.049 3.356 0.006 18.885 88.820
expression 15.9427 17.444 0.914 0.379 -22.064 53.949
Omnibus: 1.487 Durbin-Watson: 0.824
Prob(Omnibus): 0.476 Jarque-Bera (JB): 1.188
Skew: -0.609 Prob(JB): 0.552
Kurtosis: 2.354 Cond. No. 79.7

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: 05:02:49 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: 0.001
Model: OLS Adj. R-squared: -0.076
Method: Least Squares F-statistic: 0.01420
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.907
Time: 05:02:49 Log-Likelihood: -75.292
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 108.6524 126.173 0.861 0.405 -163.927 381.232
expression -2.6365 22.126 -0.119 0.907 -50.437 45.164
Omnibus: 0.697 Durbin-Watson: 1.607
Prob(Omnibus): 0.706 Jarque-Bera (JB): 0.615
Skew: 0.054 Prob(JB): 0.735
Kurtosis: 2.014 Cond. No. 73.0