LID SPN TRAP

1438427_at

Fam120b family with sequence similarity 120, member B

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
0.071 0.792 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.680
Model: OLS Adj. R-squared: 0.630
Method: Least Squares F-statistic: 13.48
Date: Thu, 21 Nov 2024 Prob (F-statistic): 6.00e-05
Time: 05:00:54 Log-Likelihood: -99.989
No. Observations: 23 AIC: 208.0
Df Residuals: 19 BIC: 212.5
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -80.7730 120.124 -0.672 0.509 -332.196 170.650
C(dose)[T.1] 284.7182 173.513 1.641 0.117 -78.448 647.885
expression 17.9689 15.972 1.125 0.275 -15.460 51.398
expression:C(dose)[T.1] -30.6932 22.969 -1.336 0.197 -78.767 17.381
Omnibus: 0.688 Durbin-Watson: 2.216
Prob(Omnibus): 0.709 Jarque-Bera (JB): 0.070
Skew: -0.095 Prob(JB): 0.966
Kurtosis: 3.191 Cond. No. 400.

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: 18.60
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.73e-05
Time: 05:00:54 Log-Likelihood: -101.02
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 30.7133 88.108 0.349 0.731 -153.077 214.504
C(dose)[T.1] 53.1368 8.786 6.048 0.000 34.809 71.465
expression 3.1277 11.701 0.267 0.792 -21.281 27.536
Omnibus: 0.549 Durbin-Watson: 1.984
Prob(Omnibus): 0.760 Jarque-Bera (JB): 0.609
Skew: 0.091 Prob(JB): 0.738
Kurtosis: 2.224 Cond. No. 155.

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: 05:00:54 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: 0.011
Model: OLS Adj. R-squared: -0.036
Method: Least Squares F-statistic: 0.2293
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.637
Time: 05:00:54 Log-Likelihood: -112.98
No. Observations: 23 AIC: 230.0
Df Residuals: 21 BIC: 232.2
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 10.6018 144.514 0.073 0.942 -289.931 311.135
expression 9.1634 19.136 0.479 0.637 -30.632 48.959
Omnibus: 3.350 Durbin-Watson: 2.589
Prob(Omnibus): 0.187 Jarque-Bera (JB): 1.769
Skew: 0.391 Prob(JB): 0.413
Kurtosis: 1.889 Cond. No. 155.

CP101

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

F-statistic p-value df difference
0.011 0.917 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.455
Model: OLS Adj. R-squared: 0.306
Method: Least Squares F-statistic: 3.055
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0737
Time: 05:00:54 Log-Likelihood: -70.755
No. Observations: 15 AIC: 149.5
Df Residuals: 11 BIC: 152.3
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 81.6411 86.019 0.949 0.363 -107.685 270.967
C(dose)[T.1] 14.3568 111.217 0.129 0.900 -230.431 259.144
expression -2.1297 12.765 -0.167 0.871 -30.226 25.966
expression:C(dose)[T.1] 5.6724 17.489 0.324 0.752 -32.821 44.166
Omnibus: 2.834 Durbin-Watson: 0.895
Prob(Omnibus): 0.242 Jarque-Bera (JB): 1.785
Skew: -0.838 Prob(JB): 0.410
Kurtosis: 2.789 Cond. No. 119.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.449
Model: OLS Adj. R-squared: 0.358
Method: Least Squares F-statistic: 4.895
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0279
Time: 05:00:54 Log-Likelihood: -70.826
No. Observations: 15 AIC: 147.7
Df Residuals: 12 BIC: 149.8
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 61.4749 57.183 1.075 0.303 -63.116 186.066
C(dose)[T.1] 49.9555 17.278 2.891 0.014 12.311 87.600
expression 0.8922 8.394 0.106 0.917 -17.397 19.181
Omnibus: 2.904 Durbin-Watson: 0.811
Prob(Omnibus): 0.234 Jarque-Bera (JB): 1.946
Skew: -0.868 Prob(JB): 0.378
Kurtosis: 2.684 Cond. No. 47.7

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: 05:00:54 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: 0.066
Model: OLS Adj. R-squared: -0.006
Method: Least Squares F-statistic: 0.9132
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.357
Time: 05:00:54 Log-Likelihood: -74.791
No. Observations: 15 AIC: 153.6
Df Residuals: 13 BIC: 155.0
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 150.5172 60.298 2.496 0.027 20.251 280.783
expression -9.1406 9.565 -0.956 0.357 -29.805 11.524
Omnibus: 2.802 Durbin-Watson: 1.460
Prob(Omnibus): 0.246 Jarque-Bera (JB): 1.103
Skew: 0.086 Prob(JB): 0.576
Kurtosis: 1.683 Cond. No. 39.6