LID SPN TRAP

1460390_at

Sorl1 sortilin-related receptor, LDLR class A repeats-containing

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
0.071 0.793 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.650
Model: OLS Adj. R-squared: 0.595
Method: Least Squares F-statistic: 11.78
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.000138
Time: 22:55:51 Log-Likelihood: -101.02
No. Observations: 23 AIC: 210.0
Df Residuals: 19 BIC: 214.6
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 90.4873 455.466 0.199 0.845 -862.815 1043.789
C(dose)[T.1] 56.7986 483.094 0.118 0.908 -954.330 1067.927
expression -4.4020 55.260 -0.080 0.937 -120.063 111.259
expression:C(dose)[T.1] -0.3555 58.521 -0.006 0.995 -122.842 122.131
Omnibus: 0.231 Durbin-Watson: 1.852
Prob(Omnibus): 0.891 Jarque-Bera (JB): 0.427
Skew: 0.079 Prob(JB): 0.808
Kurtosis: 2.352 Cond. No. 1.40e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.650
Model: OLS Adj. R-squared: 0.615
Method: Least Squares F-statistic: 18.60
Date: Thu, 03 Apr 2025 Prob (F-statistic): 2.74e-05
Time: 22:55:52 Log-Likelihood: -101.02
No. Observations: 23 AIC: 208.0
Df Residuals: 20 BIC: 211.5
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 93.0994 146.230 0.637 0.532 -211.932 398.130
C(dose)[T.1] 53.8648 8.976 6.001 0.000 35.141 72.588
expression -4.7190 17.728 -0.266 0.793 -41.699 32.261
Omnibus: 0.232 Durbin-Watson: 1.850
Prob(Omnibus): 0.891 Jarque-Bera (JB): 0.427
Skew: 0.080 Prob(JB): 0.808
Kurtosis: 2.352 Cond. No. 282.

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, 03 Apr 2025 Prob (F-statistic): 3.51e-06
Time: 22:55:52 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: 0.021
Model: OLS Adj. R-squared: -0.026
Method: Least Squares F-statistic: 0.4421
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.513
Time: 22:55:52 Log-Likelihood: -112.87
No. Observations: 23 AIC: 229.7
Df Residuals: 21 BIC: 232.0
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -76.0227 234.341 -0.324 0.749 -563.362 411.317
expression 18.7754 28.238 0.665 0.513 -39.949 77.500
Omnibus: 2.760 Durbin-Watson: 2.455
Prob(Omnibus): 0.252 Jarque-Bera (JB): 1.525
Skew: 0.333 Prob(JB): 0.467
Kurtosis: 1.928 Cond. No. 276.

CP101

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

F-statistic p-value df difference
0.557 0.470 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.478
Model: OLS Adj. R-squared: 0.336
Method: Least Squares F-statistic: 3.358
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.0589
Time: 22:55:52 Log-Likelihood: -70.424
No. Observations: 15 AIC: 148.8
Df Residuals: 11 BIC: 151.7
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 142.8972 261.803 0.546 0.596 -433.327 719.121
C(dose)[T.1] 166.2680 371.684 0.447 0.663 -651.802 984.338
expression -8.6326 29.917 -0.289 0.778 -74.479 57.214
expression:C(dose)[T.1] -13.6346 42.713 -0.319 0.756 -107.646 80.377
Omnibus: 2.171 Durbin-Watson: 0.853
Prob(Omnibus): 0.338 Jarque-Bera (JB): 1.518
Skew: -0.591 Prob(JB): 0.468
Kurtosis: 1.983 Cond. No. 543.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.473
Model: OLS Adj. R-squared: 0.385
Method: Least Squares F-statistic: 5.390
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.0214
Time: 22:55:52 Log-Likelihood: -70.493
No. Observations: 15 AIC: 147.0
Df Residuals: 12 BIC: 149.1
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 201.3729 179.903 1.119 0.285 -190.601 593.347
C(dose)[T.1] 47.7333 15.511 3.077 0.010 13.937 81.530
expression -15.3214 20.538 -0.746 0.470 -60.070 29.428
Omnibus: 2.188 Durbin-Watson: 0.929
Prob(Omnibus): 0.335 Jarque-Bera (JB): 1.626
Skew: -0.659 Prob(JB): 0.444
Kurtosis: 2.071 Cond. No. 207.

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, 03 Apr 2025 Prob (F-statistic): 0.00629
Time: 22:55:52 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: 0.057
Model: OLS Adj. R-squared: -0.015
Method: Least Squares F-statistic: 0.7928
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.389
Time: 22:55:52 Log-Likelihood: -74.856
No. Observations: 15 AIC: 153.7
Df Residuals: 13 BIC: 155.1
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 296.2878 227.773 1.301 0.216 -195.785 788.361
expression -23.3129 26.182 -0.890 0.389 -79.876 33.250
Omnibus: 0.253 Durbin-Watson: 1.486
Prob(Omnibus): 0.881 Jarque-Bera (JB): 0.428
Skew: 0.102 Prob(JB): 0.807
Kurtosis: 2.198 Cond. No. 204.