LID SPN TRAP

1460034_at

Samd4b sterile alpha motif domain containing 4B

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
1.767 0.199 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.756
Model: OLS Adj. R-squared: 0.717
Method: Least Squares F-statistic: 19.61
Date: Thu, 03 Apr 2025 Prob (F-statistic): 4.86e-06
Time: 22:54:31 Log-Likelihood: -96.890
No. Observations: 23 AIC: 201.8
Df Residuals: 19 BIC: 206.3
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 91.4444 152.390 0.600 0.556 -227.512 410.401
C(dose)[T.1] 926.4598 351.689 2.634 0.016 190.366 1662.553
expression -4.2437 17.357 -0.244 0.809 -40.573 32.086
expression:C(dose)[T.1] -96.9363 39.267 -2.469 0.023 -179.123 -14.749
Omnibus: 0.018 Durbin-Watson: 1.576
Prob(Omnibus): 0.991 Jarque-Bera (JB): 0.096
Skew: 0.007 Prob(JB): 0.953
Kurtosis: 2.683 Cond. No. 981.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.678
Model: OLS Adj. R-squared: 0.645
Method: Least Squares F-statistic: 21.01
Date: Thu, 03 Apr 2025 Prob (F-statistic): 1.22e-05
Time: 22:54:31 Log-Likelihood: -100.09
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 257.6395 153.138 1.682 0.108 -61.800 577.079
C(dose)[T.1] 58.5057 9.262 6.317 0.000 39.186 77.826
expression -23.1844 17.440 -1.329 0.199 -59.564 13.195
Omnibus: 1.208 Durbin-Watson: 1.806
Prob(Omnibus): 0.547 Jarque-Bera (JB): 0.917
Skew: -0.190 Prob(JB): 0.632
Kurtosis: 2.098 Cond. No. 329.

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: 22:54:31 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: 0.034
Model: OLS Adj. R-squared: -0.012
Method: Least Squares F-statistic: 0.7441
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.398
Time: 22:54:31 Log-Likelihood: -112.70
No. Observations: 23 AIC: 229.4
Df Residuals: 21 BIC: 231.7
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -125.0886 237.535 -0.527 0.604 -619.069 368.892
expression 23.0609 26.734 0.863 0.398 -32.536 78.658
Omnibus: 2.888 Durbin-Watson: 2.389
Prob(Omnibus): 0.236 Jarque-Bera (JB): 1.609
Skew: 0.363 Prob(JB): 0.447
Kurtosis: 1.927 Cond. No. 301.

CP101

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

F-statistic p-value df difference
0.516 0.486 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.527
Model: OLS Adj. R-squared: 0.398
Method: Least Squares F-statistic: 4.087
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.0355
Time: 22:54:31 Log-Likelihood: -69.684
No. Observations: 15 AIC: 147.4
Df Residuals: 11 BIC: 150.2
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 383.3640 241.589 1.587 0.141 -148.370 915.098
C(dose)[T.1] -348.8258 347.703 -1.003 0.337 -1114.116 416.464
expression -36.3490 27.766 -1.309 0.217 -97.461 24.763
expression:C(dose)[T.1] 46.0179 40.460 1.137 0.280 -43.034 135.070
Omnibus: 4.064 Durbin-Watson: 1.154
Prob(Omnibus): 0.131 Jarque-Bera (JB): 2.148
Skew: -0.917 Prob(JB): 0.342
Kurtosis: 3.276 Cond. No. 523.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.471
Model: OLS Adj. R-squared: 0.383
Method: Least Squares F-statistic: 5.352
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.0218
Time: 22:54:31 Log-Likelihood: -70.518
No. Observations: 15 AIC: 147.0
Df Residuals: 12 BIC: 149.2
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 194.9994 178.027 1.095 0.295 -192.889 582.888
C(dose)[T.1] 46.2327 15.955 2.898 0.013 11.469 80.996
expression -14.6773 20.441 -0.718 0.486 -59.215 29.861
Omnibus: 1.711 Durbin-Watson: 0.952
Prob(Omnibus): 0.425 Jarque-Bera (JB): 1.336
Skew: -0.658 Prob(JB): 0.513
Kurtosis: 2.363 Cond. No. 202.

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: 22:54:31 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: 0.102
Model: OLS Adj. R-squared: 0.033
Method: Least Squares F-statistic: 1.471
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.247
Time: 22:54:31 Log-Likelihood: -74.496
No. Observations: 15 AIC: 153.0
Df Residuals: 13 BIC: 154.4
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 351.1945 212.526 1.652 0.122 -107.940 810.329
expression -30.0008 24.733 -1.213 0.247 -83.433 23.431
Omnibus: 1.797 Durbin-Watson: 1.593
Prob(Omnibus): 0.407 Jarque-Bera (JB): 1.302
Skew: 0.524 Prob(JB): 0.522
Kurtosis: 2.008 Cond. No. 192.