LID SPN TRAP

1435577_at

Dab1 disabled homolog 1 (Drosophila)

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
0.589 0.452 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.704
Model: OLS Adj. R-squared: 0.658
Method: Least Squares F-statistic: 15.08
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.91e-05
Time: 03:57:38 Log-Likelihood: -99.095
No. Observations: 23 AIC: 206.2
Df Residuals: 19 BIC: 210.7
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 31.5215 175.235 0.180 0.859 -335.249 398.292
C(dose)[T.1] -767.8998 482.217 -1.592 0.128 -1777.191 241.392
expression 2.3728 18.318 0.130 0.898 -35.967 40.713
expression:C(dose)[T.1] 85.8747 50.418 1.703 0.105 -19.652 191.402
Omnibus: 0.393 Durbin-Watson: 2.056
Prob(Omnibus): 0.821 Jarque-Bera (JB): 0.507
Skew: 0.251 Prob(JB): 0.776
Kurtosis: 2.474 Cond. No. 1.29e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.659
Model: OLS Adj. R-squared: 0.625
Method: Least Squares F-statistic: 19.33
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.12e-05
Time: 03:57:38 Log-Likelihood: -100.73
No. Observations: 23 AIC: 207.5
Df Residuals: 20 BIC: 210.9
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -76.8596 170.857 -0.450 0.658 -433.260 279.541
C(dose)[T.1] 53.3098 8.644 6.168 0.000 35.280 71.340
expression 13.7084 17.859 0.768 0.452 -23.545 50.961
Omnibus: 0.839 Durbin-Watson: 1.882
Prob(Omnibus): 0.657 Jarque-Bera (JB): 0.765
Skew: 0.169 Prob(JB): 0.682
Kurtosis: 2.173 Cond. No. 383.

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: 03:57:38 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: 0.011
Model: OLS Adj. R-squared: -0.036
Method: Least Squares F-statistic: 0.2275
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.638
Time: 03:57:38 Log-Likelihood: -112.98
No. Observations: 23 AIC: 230.0
Df Residuals: 21 BIC: 232.2
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -55.7026 283.985 -0.196 0.846 -646.282 534.877
expression 14.1622 29.690 0.477 0.638 -47.581 75.905
Omnibus: 3.662 Durbin-Watson: 2.484
Prob(Omnibus): 0.160 Jarque-Bera (JB): 1.593
Skew: 0.260 Prob(JB): 0.451
Kurtosis: 1.820 Cond. No. 383.

CP101

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

F-statistic p-value df difference
0.264 0.617 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.539
Model: OLS Adj. R-squared: 0.413
Method: Least Squares F-statistic: 4.285
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0312
Time: 03:57:38 Log-Likelihood: -69.494
No. Observations: 15 AIC: 147.0
Df Residuals: 11 BIC: 149.8
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 661.8601 701.285 0.944 0.366 -881.658 2205.378
C(dose)[T.1] -1110.2958 845.608 -1.313 0.216 -2971.467 750.875
expression -60.2742 71.100 -0.848 0.415 -216.765 96.216
expression:C(dose)[T.1] 116.3280 85.154 1.366 0.199 -71.094 303.750
Omnibus: 2.072 Durbin-Watson: 1.267
Prob(Omnibus): 0.355 Jarque-Bera (JB): 1.066
Skew: -0.254 Prob(JB): 0.587
Kurtosis: 1.797 Cond. No. 1.65e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.461
Model: OLS Adj. R-squared: 0.371
Method: Least Squares F-statistic: 5.124
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0246
Time: 03:57:38 Log-Likelihood: -70.670
No. Observations: 15 AIC: 147.3
Df Residuals: 12 BIC: 149.5
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -137.9573 399.719 -0.345 0.736 -1008.869 732.955
C(dose)[T.1] 44.6447 17.911 2.493 0.028 5.620 83.670
expression 20.8257 40.514 0.514 0.617 -67.447 109.099
Omnibus: 1.866 Durbin-Watson: 0.778
Prob(Omnibus): 0.393 Jarque-Bera (JB): 1.460
Skew: -0.642 Prob(JB): 0.482
Kurtosis: 2.171 Cond. No. 520.

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: 03:57:38 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: 0.181
Model: OLS Adj. R-squared: 0.118
Method: Least Squares F-statistic: 2.881
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.113
Time: 03:57:38 Log-Likelihood: -73.799
No. Observations: 15 AIC: 151.6
Df Residuals: 13 BIC: 153.0
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -612.3296 416.054 -1.472 0.165 -1511.159 286.500
expression 70.7504 41.684 1.697 0.113 -19.303 160.803
Omnibus: 0.285 Durbin-Watson: 1.362
Prob(Omnibus): 0.867 Jarque-Bera (JB): 0.114
Skew: -0.175 Prob(JB): 0.944
Kurtosis: 2.754 Cond. No. 456.