LID SPN TRAP

1456943_a_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
0.013 0.910 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: 0.594
Method: Least Squares F-statistic: 11.74
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.000141
Time: 04:01:29 Log-Likelihood: -101.05
No. Observations: 23 AIC: 210.1
Df Residuals: 19 BIC: 214.6
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 64.6139 242.180 0.267 0.792 -442.275 571.503
C(dose)[T.1] 107.1183 484.093 0.221 0.827 -906.101 1120.337
expression -0.9984 23.229 -0.043 0.966 -49.618 47.621
expression:C(dose)[T.1] -5.4671 48.186 -0.113 0.911 -106.321 95.387
Omnibus: 0.244 Durbin-Watson: 1.906
Prob(Omnibus): 0.885 Jarque-Bera (JB): 0.436
Skew: 0.059 Prob(JB): 0.804
Kurtosis: 2.336 Cond. No. 1.29e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.649
Model: OLS Adj. R-squared: 0.614
Method: Least Squares F-statistic: 18.51
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.82e-05
Time: 04:01:29 Log-Likelihood: -101.06
No. Observations: 23 AIC: 208.1
Df Residuals: 20 BIC: 211.5
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 77.8559 206.899 0.376 0.711 -353.727 509.439
C(dose)[T.1] 52.2148 13.160 3.968 0.001 24.763 79.667
expression -2.2690 19.843 -0.114 0.910 -43.661 39.123
Omnibus: 0.310 Durbin-Watson: 1.907
Prob(Omnibus): 0.856 Jarque-Bera (JB): 0.479
Skew: 0.079 Prob(JB): 0.787
Kurtosis: 2.311 Cond. No. 487.

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: 04:01:29 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: 0.373
Model: OLS Adj. R-squared: 0.343
Method: Least Squares F-statistic: 12.51
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00196
Time: 04:01:29 Log-Likelihood: -107.73
No. Observations: 23 AIC: 219.5
Df Residuals: 21 BIC: 221.7
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 700.8967 175.748 3.988 0.001 335.408 1066.385
expression -60.9861 17.245 -3.536 0.002 -96.850 -25.122
Omnibus: 0.181 Durbin-Watson: 2.637
Prob(Omnibus): 0.914 Jarque-Bera (JB): 0.392
Skew: 0.002 Prob(JB): 0.822
Kurtosis: 2.360 Cond. No. 317.

CP101

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

F-statistic p-value df difference
3.381 0.091 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.574
Model: OLS Adj. R-squared: 0.458
Method: Least Squares F-statistic: 4.949
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0205
Time: 04:01:29 Log-Likelihood: -68.893
No. Observations: 15 AIC: 145.8
Df Residuals: 11 BIC: 148.6
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -403.2464 438.023 -0.921 0.377 -1367.329 560.836
C(dose)[T.1] -182.2995 653.947 -0.279 0.786 -1621.626 1257.027
expression 44.2400 41.159 1.075 0.305 -46.350 134.831
expression:C(dose)[T.1] 20.7148 60.917 0.340 0.740 -113.363 154.792
Omnibus: 0.001 Durbin-Watson: 1.234
Prob(Omnibus): 0.999 Jarque-Bera (JB): 0.162
Skew: -0.001 Prob(JB): 0.922
Kurtosis: 2.491 Cond. No. 1.28e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.570
Model: OLS Adj. R-squared: 0.498
Method: Least Squares F-statistic: 7.951
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00633
Time: 04:01:29 Log-Likelihood: -68.971
No. Observations: 15 AIC: 143.9
Df Residuals: 12 BIC: 146.1
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -503.8558 310.867 -1.621 0.131 -1181.176 173.464
C(dose)[T.1] 40.0127 14.773 2.709 0.019 7.826 72.199
expression 53.6966 29.204 1.839 0.091 -9.933 117.326
Omnibus: 0.106 Durbin-Watson: 1.071
Prob(Omnibus): 0.948 Jarque-Bera (JB): 0.266
Skew: -0.158 Prob(JB): 0.875
Kurtosis: 2.429 Cond. No. 486.

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: 04:01:29 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: 0.307
Model: OLS Adj. R-squared: 0.254
Method: Least Squares F-statistic: 5.759
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0321
Time: 04:01:29 Log-Likelihood: -72.550
No. Observations: 15 AIC: 149.1
Df Residuals: 13 BIC: 150.5
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -769.4906 359.771 -2.139 0.052 -1546.728 7.746
expression 80.4409 33.519 2.400 0.032 8.027 152.854
Omnibus: 1.278 Durbin-Watson: 2.050
Prob(Omnibus): 0.528 Jarque-Bera (JB): 0.550
Skew: 0.468 Prob(JB): 0.760
Kurtosis: 2.948 Cond. No. 460.