LID SPN TRAP

1457437_at

Fam163b family with sequence similarity 163, 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
1.170 0.292 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.685
Model: OLS Adj. R-squared: 0.635
Method: Least Squares F-statistic: 13.74
Date: Thu, 03 Apr 2025 Prob (F-statistic): 5.31e-05
Time: 22:47:13 Log-Likelihood: -99.837
No. Observations: 23 AIC: 207.7
Df Residuals: 19 BIC: 212.2
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -9.8521 168.954 -0.058 0.954 -363.477 343.773
C(dose)[T.1] 231.3111 187.341 1.235 0.232 -160.798 623.420
expression 10.9081 28.752 0.379 0.709 -49.270 71.086
expression:C(dose)[T.1] -31.8250 32.346 -0.984 0.338 -99.526 35.876
Omnibus: 1.906 Durbin-Watson: 2.333
Prob(Omnibus): 0.386 Jarque-Bera (JB): 1.576
Skew: 0.606 Prob(JB): 0.455
Kurtosis: 2.580 Cond. No. 377.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.668
Model: OLS Adj. R-squared: 0.635
Method: Least Squares F-statistic: 20.16
Date: Thu, 03 Apr 2025 Prob (F-statistic): 1.60e-05
Time: 22:47:13 Log-Likelihood: -100.41
No. Observations: 23 AIC: 206.8
Df Residuals: 20 BIC: 210.2
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 137.8190 77.521 1.778 0.091 -23.886 299.524
C(dose)[T.1] 47.2612 10.208 4.630 0.000 25.967 68.555
expression -14.2370 13.162 -1.082 0.292 -41.692 13.218
Omnibus: 0.312 Durbin-Watson: 1.998
Prob(Omnibus): 0.856 Jarque-Bera (JB): 0.453
Skew: 0.217 Prob(JB): 0.797
Kurtosis: 2.467 Cond. No. 107.

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, 03 Apr 2025 Prob (F-statistic): 3.51e-06
Time: 22:47:13 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: 0.313
Model: OLS Adj. R-squared: 0.280
Method: Least Squares F-statistic: 9.574
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.00550
Time: 22:47:13 Log-Likelihood: -108.79
No. Observations: 23 AIC: 221.6
Df Residuals: 21 BIC: 223.8
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 350.4849 87.713 3.996 0.001 168.076 532.894
expression -47.7658 15.437 -3.094 0.005 -79.869 -15.662
Omnibus: 2.023 Durbin-Watson: 2.495
Prob(Omnibus): 0.364 Jarque-Bera (JB): 0.718
Skew: 0.289 Prob(JB): 0.698
Kurtosis: 3.645 Cond. No. 85.9

CP101

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

F-statistic p-value df difference
0.008 0.929 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.470
Model: OLS Adj. R-squared: 0.326
Method: Least Squares F-statistic: 3.258
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.0634
Time: 22:47:13 Log-Likelihood: -70.531
No. Observations: 15 AIC: 149.1
Df Residuals: 11 BIC: 151.9
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -26.1296 203.571 -0.128 0.900 -474.185 421.926
C(dose)[T.1] 220.9782 259.095 0.853 0.412 -349.286 791.243
expression 13.5899 29.521 0.460 0.654 -51.384 78.564
expression:C(dose)[T.1] -25.3635 38.088 -0.666 0.519 -109.194 58.467
Omnibus: 1.924 Durbin-Watson: 0.742
Prob(Omnibus): 0.382 Jarque-Bera (JB): 1.476
Skew: -0.628 Prob(JB): 0.478
Kurtosis: 2.113 Cond. No. 310.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.449
Model: OLS Adj. R-squared: 0.357
Method: Least Squares F-statistic: 4.892
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.0279
Time: 22:47:13 Log-Likelihood: -70.828
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 78.7646 125.929 0.625 0.543 -195.611 353.140
C(dose)[T.1] 48.8007 16.332 2.988 0.011 13.216 84.385
expression -1.6466 18.216 -0.090 0.929 -41.335 38.042
Omnibus: 2.695 Durbin-Watson: 0.809
Prob(Omnibus): 0.260 Jarque-Bera (JB): 1.914
Skew: -0.846 Prob(JB): 0.384
Kurtosis: 2.551 Cond. No. 111.

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, 03 Apr 2025 Prob (F-statistic): 0.00629
Time: 22:47:14 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: 0.039
Model: OLS Adj. R-squared: -0.035
Method: Least Squares F-statistic: 0.5318
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.479
Time: 22:47:14 Log-Likelihood: -74.999
No. Observations: 15 AIC: 154.0
Df Residuals: 13 BIC: 155.4
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 203.3717 150.764 1.349 0.200 -122.334 529.078
expression -16.2377 22.266 -0.729 0.479 -64.341 31.866
Omnibus: 0.116 Durbin-Watson: 1.560
Prob(Omnibus): 0.944 Jarque-Bera (JB): 0.329
Skew: -0.104 Prob(JB): 0.848
Kurtosis: 2.305 Cond. No. 105.