LID SPN TRAP

1458441_at

Slc6a17 solute carrier family 6 (neurotransmitter transporter), member 17

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
0.014 0.908 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.660
Model: OLS Adj. R-squared: 0.606
Method: Least Squares F-statistic: 12.28
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.000107
Time: 05:13:45 Log-Likelihood: -100.71
No. Observations: 23 AIC: 209.4
Df Residuals: 19 BIC: 214.0
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 146.6522 147.426 0.995 0.332 -161.915 455.219
C(dose)[T.1] -109.2266 214.193 -0.510 0.616 -557.538 339.085
expression -11.7896 18.785 -0.628 0.538 -51.108 27.529
expression:C(dose)[T.1] 20.0825 26.268 0.765 0.454 -34.898 75.063
Omnibus: 0.393 Durbin-Watson: 1.836
Prob(Omnibus): 0.822 Jarque-Bera (JB): 0.522
Skew: -0.020 Prob(JB): 0.770
Kurtosis: 2.263 Cond. No. 522.

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: 18.51
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.81e-05
Time: 05:13:45 Log-Likelihood: -101.05
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 66.1201 102.066 0.648 0.524 -146.785 279.025
C(dose)[T.1] 54.2702 11.856 4.578 0.000 29.540 79.000
expression -1.5191 12.994 -0.117 0.908 -28.623 25.585
Omnibus: 0.465 Durbin-Watson: 1.873
Prob(Omnibus): 0.793 Jarque-Bera (JB): 0.560
Skew: 0.041 Prob(JB): 0.756
Kurtosis: 2.240 Cond. No. 194.

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: 05:13:45 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: 0.282
Model: OLS Adj. R-squared: 0.248
Method: Least Squares F-statistic: 8.242
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00915
Time: 05:13:45 Log-Likelihood: -109.30
No. Observations: 23 AIC: 222.6
Df Residuals: 21 BIC: 224.9
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -233.6565 109.327 -2.137 0.045 -461.015 -6.298
expression 38.5220 13.418 2.871 0.009 10.617 66.427
Omnibus: 1.853 Durbin-Watson: 2.513
Prob(Omnibus): 0.396 Jarque-Bera (JB): 1.518
Skew: 0.482 Prob(JB): 0.468
Kurtosis: 2.190 Cond. No. 148.

CP101

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

F-statistic p-value df difference
0.059 0.812 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.536
Model: OLS Adj. R-squared: 0.410
Method: Least Squares F-statistic: 4.240
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0321
Time: 05:13:45 Log-Likelihood: -69.537
No. Observations: 15 AIC: 147.1
Df Residuals: 11 BIC: 149.9
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -340.1469 291.527 -1.167 0.268 -981.794 301.500
C(dose)[T.1] 500.8513 318.786 1.571 0.144 -200.793 1202.495
expression 53.3288 38.117 1.399 0.189 -30.567 137.225
expression:C(dose)[T.1] -59.1136 41.685 -1.418 0.184 -150.861 32.634
Omnibus: 2.545 Durbin-Watson: 1.441
Prob(Omnibus): 0.280 Jarque-Bera (JB): 1.274
Skew: -0.713 Prob(JB): 0.529
Kurtosis: 3.068 Cond. No. 507.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.451
Model: OLS Adj. R-squared: 0.360
Method: Least Squares F-statistic: 4.938
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0272
Time: 05:13:45 Log-Likelihood: -70.796
No. Observations: 15 AIC: 147.6
Df Residuals: 12 BIC: 149.7
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 37.6178 123.320 0.305 0.766 -231.073 306.309
C(dose)[T.1] 49.2853 15.705 3.138 0.009 15.066 83.504
expression 3.9006 16.066 0.243 0.812 -31.104 38.905
Omnibus: 2.824 Durbin-Watson: 0.809
Prob(Omnibus): 0.244 Jarque-Bera (JB): 1.990
Skew: -0.866 Prob(JB): 0.370
Kurtosis: 2.573 Cond. No. 123.

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: 05:13:45 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: 0.01714
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.898
Time: 05:13:45 Log-Likelihood: -75.290
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 72.8680 159.205 0.458 0.655 -271.073 416.809
expression 2.7257 20.822 0.131 0.898 -42.257 47.708
Omnibus: 0.836 Durbin-Watson: 1.631
Prob(Omnibus): 0.658 Jarque-Bera (JB): 0.663
Skew: 0.069 Prob(JB): 0.718
Kurtosis: 1.979 Cond. No. 122.