LID SPN TRAP

1437149_at

Slc6a6 solute carrier family 6 (neurotransmitter transporter, taurine), member 6

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
1.146 0.297 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.678
Model: OLS Adj. R-squared: 0.628
Method: Least Squares F-statistic: 13.36
Date: Tue, 03 Dec 2024 Prob (F-statistic): 6.34e-05
Time: 11:42:53 Log-Likelihood: -100.06
No. Observations: 23 AIC: 208.1
Df Residuals: 19 BIC: 212.7
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 115.6450 156.378 0.740 0.469 -211.659 442.949
C(dose)[T.1] 259.1904 263.912 0.982 0.338 -293.184 811.565
expression -6.9930 17.787 -0.393 0.699 -44.221 30.235
expression:C(dose)[T.1] -23.5785 30.118 -0.783 0.443 -86.616 39.459
Omnibus: 0.215 Durbin-Watson: 1.621
Prob(Omnibus): 0.898 Jarque-Bera (JB): 0.416
Skew: -0.082 Prob(JB): 0.812
Kurtosis: 2.362 Cond. No. 663.

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: 20.13
Date: Tue, 03 Dec 2024 Prob (F-statistic): 1.62e-05
Time: 11:42:53 Log-Likelihood: -100.42
No. Observations: 23 AIC: 206.8
Df Residuals: 20 BIC: 210.3
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 187.8918 125.017 1.503 0.148 -72.889 448.672
C(dose)[T.1] 52.6926 8.550 6.163 0.000 34.857 70.528
expression -15.2164 14.214 -1.071 0.297 -44.867 14.434
Omnibus: 0.899 Durbin-Watson: 1.508
Prob(Omnibus): 0.638 Jarque-Bera (JB): 0.740
Skew: 0.002 Prob(JB): 0.691
Kurtosis: 2.121 Cond. No. 261.

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: Tue, 03 Dec 2024 Prob (F-statistic): 3.51e-06
Time: 11:42:53 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: 0.038
Model: OLS Adj. R-squared: -0.008
Method: Least Squares F-statistic: 0.8239
Date: Tue, 03 Dec 2024 Prob (F-statistic): 0.374
Time: 11:42:53 Log-Likelihood: -112.66
No. Observations: 23 AIC: 229.3
Df Residuals: 21 BIC: 231.6
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 267.1576 206.627 1.293 0.210 -162.547 696.862
expression -21.3846 23.560 -0.908 0.374 -70.380 27.611
Omnibus: 3.793 Durbin-Watson: 2.333
Prob(Omnibus): 0.150 Jarque-Bera (JB): 1.526
Skew: 0.190 Prob(JB): 0.466
Kurtosis: 1.797 Cond. No. 259.

CP101

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

F-statistic p-value df difference
1.021 0.332 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.648
Model: OLS Adj. R-squared: 0.552
Method: Least Squares F-statistic: 6.747
Date: Tue, 03 Dec 2024 Prob (F-statistic): 0.00759
Time: 11:42:53 Log-Likelihood: -67.471
No. Observations: 15 AIC: 142.9
Df Residuals: 11 BIC: 145.8
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -114.6308 427.613 -0.268 0.794 -1055.801 826.539
C(dose)[T.1] 1576.8420 694.769 2.270 0.044 47.665 3106.019
expression 18.6598 43.816 0.426 0.678 -77.779 115.099
expression:C(dose)[T.1] -158.5321 71.826 -2.207 0.049 -316.621 -0.444
Omnibus: 3.462 Durbin-Watson: 0.918
Prob(Omnibus): 0.177 Jarque-Bera (JB): 1.691
Skew: -0.810 Prob(JB): 0.429
Kurtosis: 3.288 Cond. No. 1.30e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.492
Model: OLS Adj. R-squared: 0.407
Method: Least Squares F-statistic: 5.810
Date: Tue, 03 Dec 2024 Prob (F-statistic): 0.0172
Time: 11:42:53 Log-Likelihood: -70.221
No. Observations: 15 AIC: 146.4
Df Residuals: 12 BIC: 148.6
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 460.9795 389.733 1.183 0.260 -388.175 1310.134
C(dose)[T.1] 43.6842 16.065 2.719 0.019 8.681 78.687
expression -40.3362 39.929 -1.010 0.332 -127.334 46.661
Omnibus: 4.002 Durbin-Watson: 0.944
Prob(Omnibus): 0.135 Jarque-Bera (JB): 2.768
Skew: -1.042 Prob(JB): 0.251
Kurtosis: 2.702 Cond. No. 507.

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: Tue, 03 Dec 2024 Prob (F-statistic): 0.00629
Time: 11:42:53 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: 0.179
Model: OLS Adj. R-squared: 0.116
Method: Least Squares F-statistic: 2.833
Date: Tue, 03 Dec 2024 Prob (F-statistic): 0.116
Time: 11:42:53 Log-Likelihood: -73.821
No. Observations: 15 AIC: 151.6
Df Residuals: 13 BIC: 153.1
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 841.3886 444.296 1.894 0.081 -118.455 1801.232
expression -77.2130 45.870 -1.683 0.116 -176.309 21.883
Omnibus: 2.460 Durbin-Watson: 1.945
Prob(Omnibus): 0.292 Jarque-Bera (JB): 1.455
Skew: -0.759 Prob(JB): 0.483
Kurtosis: 2.846 Cond. No. 472.