LID SPN TRAP

1457800_at

Slc1a2 solute carrier family 1 (glial high affinity glutamate transporter), member 2

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
0.741 0.400 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.672
Model: OLS Adj. R-squared: 0.620
Method: Least Squares F-statistic: 12.96
Date: Tue, 03 Dec 2024 Prob (F-statistic): 7.67e-05
Time: 11:43:55 Log-Likelihood: -100.29
No. Observations: 23 AIC: 208.6
Df Residuals: 19 BIC: 213.1
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 79.5434 206.500 0.385 0.704 -352.666 511.753
C(dose)[T.1] -145.0942 256.367 -0.566 0.578 -681.676 391.488
expression -2.8145 22.931 -0.123 0.904 -50.809 45.180
expression:C(dose)[T.1] 21.7387 28.306 0.768 0.452 -37.506 80.984
Omnibus: 0.006 Durbin-Watson: 1.993
Prob(Omnibus): 0.997 Jarque-Bera (JB): 0.139
Skew: -0.028 Prob(JB): 0.933
Kurtosis: 2.623 Cond. No. 754.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.662
Model: OLS Adj. R-squared: 0.628
Method: Least Squares F-statistic: 19.55
Date: Tue, 03 Dec 2024 Prob (F-statistic): 1.97e-05
Time: 11:43:55 Log-Likelihood: -100.64
No. Observations: 23 AIC: 207.3
Df Residuals: 20 BIC: 210.7
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -48.8762 119.919 -0.408 0.688 -299.022 201.270
C(dose)[T.1] 51.6744 8.826 5.855 0.000 33.264 70.085
expression 11.4518 13.305 0.861 0.400 -16.303 39.206
Omnibus: 0.102 Durbin-Watson: 1.990
Prob(Omnibus): 0.950 Jarque-Bera (JB): 0.325
Skew: -0.040 Prob(JB): 0.850
Kurtosis: 2.424 Cond. No. 257.

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: 11:43:55 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: 0.082
Model: OLS Adj. R-squared: 0.038
Method: Least Squares F-statistic: 1.865
Date: Tue, 03 Dec 2024 Prob (F-statistic): 0.187
Time: 11:43:55 Log-Likelihood: -112.13
No. Observations: 23 AIC: 228.3
Df Residuals: 21 BIC: 230.5
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -178.8419 189.463 -0.944 0.356 -572.852 215.168
expression 28.5037 20.873 1.366 0.187 -14.903 71.911
Omnibus: 2.259 Durbin-Watson: 2.411
Prob(Omnibus): 0.323 Jarque-Bera (JB): 1.156
Skew: 0.111 Prob(JB): 0.561
Kurtosis: 1.924 Cond. No. 252.

CP101

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

F-statistic p-value df difference
2.965 0.111 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.562
Model: OLS Adj. R-squared: 0.442
Method: Least Squares F-statistic: 4.699
Date: Tue, 03 Dec 2024 Prob (F-statistic): 0.0239
Time: 11:43:55 Log-Likelihood: -69.113
No. Observations: 15 AIC: 146.2
Df Residuals: 11 BIC: 149.1
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 393.0675 222.243 1.769 0.105 -96.087 882.222
C(dose)[T.1] -59.3343 344.275 -0.172 0.866 -817.079 698.410
expression -32.3795 22.073 -1.467 0.170 -80.961 16.202
expression:C(dose)[T.1] 10.5537 34.422 0.307 0.765 -65.209 86.316
Omnibus: 2.415 Durbin-Watson: 0.930
Prob(Omnibus): 0.299 Jarque-Bera (JB): 1.553
Skew: -0.776 Prob(JB): 0.460
Kurtosis: 2.722 Cond. No. 608.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.558
Model: OLS Adj. R-squared: 0.484
Method: Least Squares F-statistic: 7.574
Date: Tue, 03 Dec 2024 Prob (F-statistic): 0.00746
Time: 11:43:55 Log-Likelihood: -69.177
No. Observations: 15 AIC: 144.4
Df Residuals: 12 BIC: 146.5
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 349.4244 164.105 2.129 0.055 -8.129 706.978
C(dose)[T.1] 46.1223 14.207 3.246 0.007 15.167 77.077
expression -28.0399 16.285 -1.722 0.111 -63.523 7.443
Omnibus: 2.526 Durbin-Watson: 0.844
Prob(Omnibus): 0.283 Jarque-Bera (JB): 1.641
Skew: -0.797 Prob(JB): 0.440
Kurtosis: 2.714 Cond. No. 236.

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: 11:43:55 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: 0.170
Model: OLS Adj. R-squared: 0.106
Method: Least Squares F-statistic: 2.658
Date: Tue, 03 Dec 2024 Prob (F-statistic): 0.127
Time: 11:43:55 Log-Likelihood: -73.905
No. Observations: 15 AIC: 151.8
Df Residuals: 13 BIC: 153.2
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 440.4538 212.903 2.069 0.059 -19.496 900.403
expression -34.6840 21.273 -1.630 0.127 -80.642 11.274
Omnibus: 4.533 Durbin-Watson: 1.703
Prob(Omnibus): 0.104 Jarque-Bera (JB): 1.599
Skew: 0.365 Prob(JB): 0.450
Kurtosis: 1.577 Cond. No. 232.