LID SPN TRAP

1452142_at

Slc6a1 solute carrier family 6 (neurotransmitter transporter, GABA), member 1

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
1.010 0.327 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.671
Model: OLS Adj. R-squared: 0.619
Method: Least Squares F-statistic: 12.91
Date: Thu, 21 Nov 2024 Prob (F-statistic): 7.88e-05
Time: 04:34:28 Log-Likelihood: -100.33
No. Observations: 23 AIC: 208.7
Df Residuals: 19 BIC: 213.2
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 143.6978 214.171 0.671 0.510 -304.567 591.963
C(dose)[T.1] 223.0508 328.615 0.679 0.505 -464.749 910.851
expression -9.4933 22.711 -0.418 0.681 -57.028 38.041
expression:C(dose)[T.1] -18.8864 35.496 -0.532 0.601 -93.181 55.408
Omnibus: 0.587 Durbin-Watson: 1.735
Prob(Omnibus): 0.746 Jarque-Bera (JB): 0.651
Skew: 0.173 Prob(JB): 0.722
Kurtosis: 2.252 Cond. No. 884.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.666
Model: OLS Adj. R-squared: 0.633
Method: Least Squares F-statistic: 19.93
Date: Thu, 21 Nov 2024 Prob (F-statistic): 1.73e-05
Time: 04:34:28 Log-Likelihood: -100.50
No. Observations: 23 AIC: 207.0
Df Residuals: 20 BIC: 210.4
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 216.5783 161.664 1.340 0.195 -120.647 553.804
C(dose)[T.1] 48.2872 9.923 4.866 0.000 27.589 68.986
expression -17.2248 17.138 -1.005 0.327 -52.975 18.525
Omnibus: 0.754 Durbin-Watson: 1.756
Prob(Omnibus): 0.686 Jarque-Bera (JB): 0.740
Skew: 0.192 Prob(JB): 0.691
Kurtosis: 2.210 Cond. No. 356.

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: 04:34:28 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: 0.270
Model: OLS Adj. R-squared: 0.236
Method: Least Squares F-statistic: 7.781
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0110
Time: 04:34:28 Log-Likelihood: -109.48
No. Observations: 23 AIC: 223.0
Df Residuals: 21 BIC: 225.2
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 631.8567 198.029 3.191 0.004 220.033 1043.681
expression -59.4572 21.314 -2.790 0.011 -103.783 -15.131
Omnibus: 2.059 Durbin-Watson: 2.510
Prob(Omnibus): 0.357 Jarque-Bera (JB): 1.391
Skew: 0.363 Prob(JB): 0.499
Kurtosis: 2.038 Cond. No. 302.

CP101

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

F-statistic p-value df difference
5.234 0.041 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.640
Model: OLS Adj. R-squared: 0.541
Method: Least Squares F-statistic: 6.509
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00858
Time: 04:34:28 Log-Likelihood: -67.645
No. Observations: 15 AIC: 143.3
Df Residuals: 11 BIC: 146.1
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 373.9913 241.375 1.549 0.150 -157.271 905.254
C(dose)[T.1] 360.7001 386.067 0.934 0.370 -489.027 1210.428
expression -32.1099 25.262 -1.271 0.230 -87.710 23.490
expression:C(dose)[T.1] -34.9670 41.309 -0.846 0.415 -125.888 55.954
Omnibus: 3.448 Durbin-Watson: 1.557
Prob(Omnibus): 0.178 Jarque-Bera (JB): 1.228
Skew: -0.141 Prob(JB): 0.541
Kurtosis: 1.627 Cond. No. 694.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.616
Model: OLS Adj. R-squared: 0.552
Method: Least Squares F-statistic: 9.633
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00320
Time: 04:34:29 Log-Likelihood: -68.118
No. Observations: 15 AIC: 142.2
Df Residuals: 12 BIC: 144.4
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 498.8338 188.804 2.642 0.021 87.465 910.203
C(dose)[T.1] 34.1492 14.688 2.325 0.038 2.146 66.152
expression -45.1861 19.750 -2.288 0.041 -88.218 -2.154
Omnibus: 3.210 Durbin-Watson: 1.740
Prob(Omnibus): 0.201 Jarque-Bera (JB): 1.347
Skew: -0.323 Prob(JB): 0.510
Kurtosis: 1.681 Cond. No. 274.

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: 04:34:29 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: 0.443
Model: OLS Adj. R-squared: 0.400
Method: Least Squares F-statistic: 10.35
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00674
Time: 04:34:29 Log-Likelihood: -70.907
No. Observations: 15 AIC: 145.8
Df Residuals: 13 BIC: 147.2
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 709.6872 191.609 3.704 0.003 295.742 1123.632
expression -65.7461 20.434 -3.218 0.007 -109.891 -21.602
Omnibus: 0.043 Durbin-Watson: 2.262
Prob(Omnibus): 0.979 Jarque-Bera (JB): 0.101
Skew: -0.033 Prob(JB): 0.951
Kurtosis: 2.604 Cond. No. 240.