LID SPN TRAP

1458114_at

Samd12 sterile alpha motif domain containing 12

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
0.007 0.935 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.665
Model: OLS Adj. R-squared: 0.613
Method: Least Squares F-statistic: 12.60
Date: Thu, 21 Nov 2024 Prob (F-statistic): 9.16e-05
Time: 05:06:38 Log-Likelihood: -100.51
No. Observations: 23 AIC: 209.0
Df Residuals: 19 BIC: 213.6
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -34.9377 108.562 -0.322 0.751 -262.161 192.286
C(dose)[T.1] 166.0282 118.372 1.403 0.177 -81.728 413.784
expression 15.0894 18.347 0.822 0.421 -23.312 53.490
expression:C(dose)[T.1] -19.7117 20.515 -0.961 0.349 -62.650 23.227
Omnibus: 0.067 Durbin-Watson: 1.993
Prob(Omnibus): 0.967 Jarque-Bera (JB): 0.264
Skew: -0.086 Prob(JB): 0.876
Kurtosis: 2.503 Cond. No. 226.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.649
Model: OLS Adj. R-squared: 0.614
Method: Least Squares F-statistic: 18.50
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.82e-05
Time: 05:06:38 Log-Likelihood: -101.06
No. Observations: 23 AIC: 208.1
Df Residuals: 20 BIC: 211.5
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 58.2049 48.781 1.193 0.247 -43.550 159.960
C(dose)[T.1] 52.7864 11.017 4.792 0.000 29.806 75.766
expression -0.6765 8.193 -0.083 0.935 -17.767 16.414
Omnibus: 0.238 Durbin-Watson: 1.885
Prob(Omnibus): 0.888 Jarque-Bera (JB): 0.432
Skew: 0.043 Prob(JB): 0.806
Kurtosis: 2.334 Cond. No. 64.7

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: 05:06:38 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: 0.246
Model: OLS Adj. R-squared: 0.211
Method: Least Squares F-statistic: 6.868
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0160
Time: 05:06:38 Log-Likelihood: -109.85
No. Observations: 23 AIC: 223.7
Df Residuals: 21 BIC: 226.0
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 214.6028 51.850 4.139 0.000 106.775 322.431
expression -24.4422 9.327 -2.621 0.016 -43.838 -5.046
Omnibus: 0.485 Durbin-Watson: 2.068
Prob(Omnibus): 0.785 Jarque-Bera (JB): 0.583
Skew: 0.118 Prob(JB): 0.747
Kurtosis: 2.257 Cond. No. 47.5

CP101

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

F-statistic p-value df difference
1.917 0.191 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.568
Model: OLS Adj. R-squared: 0.450
Method: Least Squares F-statistic: 4.825
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0221
Time: 05:06:38 Log-Likelihood: -69.001
No. Observations: 15 AIC: 146.0
Df Residuals: 11 BIC: 148.8
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 362.6170 170.721 2.124 0.057 -13.138 738.372
C(dose)[T.1] -208.7801 249.369 -0.837 0.420 -757.637 340.077
expression -48.8888 28.220 -1.732 0.111 -111.000 13.223
expression:C(dose)[T.1] 42.8730 40.709 1.053 0.315 -46.728 132.474
Omnibus: 5.239 Durbin-Watson: 1.375
Prob(Omnibus): 0.073 Jarque-Bera (JB): 2.652
Skew: -0.974 Prob(JB): 0.265
Kurtosis: 3.672 Cond. No. 285.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.525
Model: OLS Adj. R-squared: 0.445
Method: Least Squares F-statistic: 6.623
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0115
Time: 05:06:38 Log-Likelihood: -69.722
No. Observations: 15 AIC: 145.4
Df Residuals: 12 BIC: 147.6
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 238.2241 123.825 1.924 0.078 -31.568 508.017
C(dose)[T.1] 53.3758 14.924 3.576 0.004 20.859 85.893
expression -28.2870 20.432 -1.384 0.191 -72.803 16.229
Omnibus: 8.795 Durbin-Watson: 1.094
Prob(Omnibus): 0.012 Jarque-Bera (JB): 5.145
Skew: -1.242 Prob(JB): 0.0763
Kurtosis: 4.438 Cond. No. 107.

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: 05:06:38 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: 0.018
Model: OLS Adj. R-squared: -0.057
Method: Least Squares F-statistic: 0.2389
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.633
Time: 05:06:38 Log-Likelihood: -75.163
No. Observations: 15 AIC: 154.3
Df Residuals: 13 BIC: 155.7
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 176.2805 169.316 1.041 0.317 -189.504 542.065
expression -13.5062 27.632 -0.489 0.633 -73.201 46.188
Omnibus: 1.622 Durbin-Watson: 1.781
Prob(Omnibus): 0.444 Jarque-Bera (JB): 0.908
Skew: 0.167 Prob(JB): 0.635
Kurtosis: 1.842 Cond. No. 106.