LID SPN TRAP

1439968_x_at

Dbndd2 dysbindin (dystrobrevin binding protein 1) domain containing 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
1.164 0.293 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.677
Model: OLS Adj. R-squared: 0.626
Method: Least Squares F-statistic: 13.28
Date: Wed, 29 Jan 2025 Prob (F-statistic): 6.60e-05
Time: 00:59:22 Log-Likelihood: -100.11
No. Observations: 23 AIC: 208.2
Df Residuals: 19 BIC: 212.8
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 181.5725 232.833 0.780 0.445 -305.753 668.898
C(dose)[T.1] 356.1627 437.796 0.814 0.426 -560.155 1272.480
expression -12.2780 22.438 -0.547 0.591 -59.241 34.685
expression:C(dose)[T.1] -31.2029 43.672 -0.714 0.484 -122.610 60.204
Omnibus: 0.485 Durbin-Watson: 2.121
Prob(Omnibus): 0.785 Jarque-Bera (JB): 0.239
Skew: 0.241 Prob(JB): 0.887
Kurtosis: 2.870 Cond. No. 1.22e+03

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: 20.15
Date: Wed, 29 Jan 2025 Prob (F-statistic): 1.61e-05
Time: 00:59:22 Log-Likelihood: -100.41
No. Observations: 23 AIC: 206.8
Df Residuals: 20 BIC: 210.2
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 267.0133 197.317 1.353 0.191 -144.582 678.608
C(dose)[T.1] 43.4982 12.483 3.485 0.002 17.459 69.538
expression -20.5145 19.013 -1.079 0.293 -60.175 19.146
Omnibus: 0.416 Durbin-Watson: 2.049
Prob(Omnibus): 0.812 Jarque-Bera (JB): 0.292
Skew: 0.251 Prob(JB): 0.864
Kurtosis: 2.769 Cond. No. 476.

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: Wed, 29 Jan 2025 Prob (F-statistic): 3.51e-06
Time: 00:59:22 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: 0.467
Model: OLS Adj. R-squared: 0.442
Method: Least Squares F-statistic: 18.40
Date: Wed, 29 Jan 2025 Prob (F-statistic): 0.000325
Time: 00:59:22 Log-Likelihood: -105.87
No. Observations: 23 AIC: 215.7
Df Residuals: 21 BIC: 218.0
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 778.7365 163.038 4.776 0.000 439.679 1117.794
expression -68.9097 16.064 -4.290 0.000 -102.317 -35.503
Omnibus: 0.115 Durbin-Watson: 2.484
Prob(Omnibus): 0.944 Jarque-Bera (JB): 0.238
Skew: 0.143 Prob(JB): 0.888
Kurtosis: 2.592 Cond. No. 317.

CP101

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

F-statistic p-value df difference
2.826 0.119 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.568
Model: OLS Adj. R-squared: 0.451
Method: Least Squares F-statistic: 4.831
Date: Wed, 29 Jan 2025 Prob (F-statistic): 0.0221
Time: 00:59:22 Log-Likelihood: -68.997
No. Observations: 15 AIC: 146.0
Df Residuals: 11 BIC: 148.8
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -378.9125 500.735 -0.757 0.465 -1481.023 723.198
C(dose)[T.1] -452.5483 805.680 -0.562 0.586 -2225.837 1320.740
expression 42.0450 47.158 0.892 0.392 -61.750 145.840
expression:C(dose)[T.1] 45.9383 75.193 0.611 0.554 -119.560 211.436
Omnibus: 0.218 Durbin-Watson: 1.353
Prob(Omnibus): 0.897 Jarque-Bera (JB): 0.400
Skew: -0.163 Prob(JB): 0.819
Kurtosis: 2.270 Cond. No. 1.52e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.554
Model: OLS Adj. R-squared: 0.479
Method: Least Squares F-statistic: 7.448
Date: Wed, 29 Jan 2025 Prob (F-statistic): 0.00789
Time: 00:59:22 Log-Likelihood: -69.247
No. Observations: 15 AIC: 144.5
Df Residuals: 12 BIC: 146.6
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -570.7317 379.749 -1.503 0.159 -1398.135 256.671
C(dose)[T.1] 39.5813 15.272 2.592 0.024 6.307 72.856
expression 60.1142 35.759 1.681 0.119 -17.798 138.026
Omnibus: 0.591 Durbin-Watson: 1.029
Prob(Omnibus): 0.744 Jarque-Bera (JB): 0.636
Skew: -0.323 Prob(JB): 0.728
Kurtosis: 2.225 Cond. No. 581.

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: Wed, 29 Jan 2025 Prob (F-statistic): 0.00629
Time: 00:59:22 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: 0.304
Model: OLS Adj. R-squared: 0.251
Method: Least Squares F-statistic: 5.681
Date: Wed, 29 Jan 2025 Prob (F-statistic): 0.0331
Time: 00:59:22 Log-Likelihood: -72.581
No. Observations: 15 AIC: 149.2
Df Residuals: 13 BIC: 150.6
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -921.0578 425.826 -2.163 0.050 -1840.999 -1.116
expression 94.8242 39.785 2.383 0.033 8.874 180.774
Omnibus: 0.084 Durbin-Watson: 2.028
Prob(Omnibus): 0.959 Jarque-Bera (JB): 0.173
Skew: 0.132 Prob(JB): 0.917
Kurtosis: 2.544 Cond. No. 542.