LID SPN TRAP

1458394_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
0.815 0.378 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.664
Model: OLS Adj. R-squared: 0.611
Method: Least Squares F-statistic: 12.53
Date: Mon, 03 Feb 2025 Prob (F-statistic): 9.46e-05
Time: 23:51:08 Log-Likelihood: -100.55
No. Observations: 23 AIC: 209.1
Df Residuals: 19 BIC: 213.6
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -33.7839 186.730 -0.181 0.858 -424.615 357.047
C(dose)[T.1] -38.5915 292.540 -0.132 0.896 -650.885 573.702
expression 9.8205 20.829 0.471 0.643 -33.776 53.417
expression:C(dose)[T.1] 9.1420 31.571 0.290 0.775 -56.936 75.220
Omnibus: 0.027 Durbin-Watson: 1.888
Prob(Omnibus): 0.986 Jarque-Bera (JB): 0.217
Skew: -0.055 Prob(JB): 0.897
Kurtosis: 2.537 Cond. No. 783.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.663
Model: OLS Adj. R-squared: 0.629
Method: Least Squares F-statistic: 19.66
Date: Mon, 03 Feb 2025 Prob (F-statistic): 1.90e-05
Time: 23:51:08 Log-Likelihood: -100.60
No. Observations: 23 AIC: 207.2
Df Residuals: 20 BIC: 210.6
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -69.4400 137.127 -0.506 0.618 -355.482 216.602
C(dose)[T.1] 46.0482 11.795 3.904 0.001 21.445 70.652
expression 13.8000 15.290 0.903 0.378 -18.094 45.694
Omnibus: 0.016 Durbin-Watson: 1.860
Prob(Omnibus): 0.992 Jarque-Bera (JB): 0.213
Skew: -0.027 Prob(JB): 0.899
Kurtosis: 2.532 Cond. No. 299.

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: Mon, 03 Feb 2025 Prob (F-statistic): 3.51e-06
Time: 23:51:08 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: 0.406
Model: OLS Adj. R-squared: 0.378
Method: Least Squares F-statistic: 14.34
Date: Mon, 03 Feb 2025 Prob (F-statistic): 0.00108
Time: 23:51:08 Log-Likelihood: -107.12
No. Observations: 23 AIC: 218.2
Df Residuals: 21 BIC: 220.5
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -423.9485 133.112 -3.185 0.004 -700.770 -147.127
expression 54.6710 14.436 3.787 0.001 24.649 84.693
Omnibus: 2.744 Durbin-Watson: 1.958
Prob(Omnibus): 0.254 Jarque-Bera (JB): 1.232
Skew: 0.036 Prob(JB): 0.540
Kurtosis: 1.868 Cond. No. 223.

CP101

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

F-statistic p-value df difference
1.077 0.320 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.503
Model: OLS Adj. R-squared: 0.367
Method: Least Squares F-statistic: 3.705
Date: Mon, 03 Feb 2025 Prob (F-statistic): 0.0460
Time: 23:51:08 Log-Likelihood: -70.062
No. Observations: 15 AIC: 148.1
Df Residuals: 11 BIC: 151.0
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -131.6327 194.018 -0.678 0.512 -558.663 295.397
C(dose)[T.1] 173.0982 282.635 0.612 0.553 -448.978 795.174
expression 22.9712 22.350 1.028 0.326 -26.222 72.164
expression:C(dose)[T.1] -14.1654 32.830 -0.431 0.674 -86.424 58.093
Omnibus: 2.360 Durbin-Watson: 0.683
Prob(Omnibus): 0.307 Jarque-Bera (JB): 1.684
Skew: -0.787 Prob(JB): 0.431
Kurtosis: 2.535 Cond. No. 414.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.494
Model: OLS Adj. R-squared: 0.410
Method: Least Squares F-statistic: 5.862
Date: Mon, 03 Feb 2025 Prob (F-statistic): 0.0167
Time: 23:51:08 Log-Likelihood: -70.188
No. Observations: 15 AIC: 146.4
Df Residuals: 12 BIC: 148.5
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -74.7388 137.414 -0.544 0.596 -374.137 224.660
C(dose)[T.1] 51.3369 15.218 3.373 0.006 18.180 84.494
expression 16.4058 15.806 1.038 0.320 -18.033 50.845
Omnibus: 2.279 Durbin-Watson: 0.697
Prob(Omnibus): 0.320 Jarque-Bera (JB): 1.667
Skew: -0.774 Prob(JB): 0.434
Kurtosis: 2.480 Cond. No. 160.

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: Mon, 03 Feb 2025 Prob (F-statistic): 0.00629
Time: 23:51:08 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: 0.014
Model: OLS Adj. R-squared: -0.061
Method: Least Squares F-statistic: 0.1911
Date: Mon, 03 Feb 2025 Prob (F-statistic): 0.669
Time: 23:51:08 Log-Likelihood: -75.191
No. Observations: 15 AIC: 154.4
Df Residuals: 13 BIC: 155.8
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 14.7555 180.816 0.082 0.936 -375.873 405.384
expression 9.1799 21.002 0.437 0.669 -36.192 54.552
Omnibus: 1.652 Durbin-Watson: 1.697
Prob(Omnibus): 0.438 Jarque-Bera (JB): 0.904
Skew: 0.145 Prob(JB): 0.636
Kurtosis: 1.833 Cond. No. 156.