LID SPN TRAP

1431798_a_at

Syde1 synapse defective 1, Rho GTPase, homolog 1 (C. elegans)

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
0.864 0.364 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.699
Model: OLS Adj. R-squared: 0.651
Method: Least Squares F-statistic: 14.70
Date: Thu, 21 Nov 2024 Prob (F-statistic): 3.44e-05
Time: 04:45:49 Log-Likelihood: -99.299
No. Observations: 23 AIC: 206.6
Df Residuals: 19 BIC: 211.1
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 113.2478 37.583 3.013 0.007 34.586 191.910
C(dose)[T.1] -54.4028 72.574 -0.750 0.463 -206.302 97.496
expression -25.0774 15.775 -1.590 0.128 -58.094 7.939
expression:C(dose)[T.1] 45.7931 30.655 1.494 0.152 -18.368 109.955
Omnibus: 0.764 Durbin-Watson: 2.061
Prob(Omnibus): 0.682 Jarque-Bera (JB): 0.690
Skew: -0.009 Prob(JB): 0.708
Kurtosis: 2.152 Cond. No. 57.4

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.664
Model: OLS Adj. R-squared: 0.630
Method: Least Squares F-statistic: 19.73
Date: Thu, 21 Nov 2024 Prob (F-statistic): 1.86e-05
Time: 04:45:49 Log-Likelihood: -100.58
No. Observations: 23 AIC: 207.2
Df Residuals: 20 BIC: 210.6
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 84.6992 33.342 2.540 0.019 15.148 154.250
C(dose)[T.1] 53.2932 8.587 6.207 0.000 35.382 71.204
expression -12.9512 13.936 -0.929 0.364 -42.021 16.119
Omnibus: 0.001 Durbin-Watson: 2.016
Prob(Omnibus): 1.000 Jarque-Bera (JB): 0.162
Skew: 0.007 Prob(JB): 0.922
Kurtosis: 2.589 Cond. No. 22.0

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: 04:45:49 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: 0.016
Model: OLS Adj. R-squared: -0.031
Method: Least Squares F-statistic: 0.3331
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.570
Time: 04:45:49 Log-Likelihood: -112.92
No. Observations: 23 AIC: 229.8
Df Residuals: 21 BIC: 232.1
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 111.3067 55.198 2.016 0.057 -3.485 226.098
expression -13.4271 23.264 -0.577 0.570 -61.807 34.953
Omnibus: 3.504 Durbin-Watson: 2.638
Prob(Omnibus): 0.173 Jarque-Bera (JB): 1.824
Skew: 0.402 Prob(JB): 0.402
Kurtosis: 1.878 Cond. No. 21.5

CP101

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

F-statistic p-value df difference
0.919 0.357 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.538
Model: OLS Adj. R-squared: 0.413
Method: Least Squares F-statistic: 4.277
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0313
Time: 04:45:49 Log-Likelihood: -69.502
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 128.8623 47.329 2.723 0.020 24.691 233.033
C(dose)[T.1] -67.1279 104.013 -0.645 0.532 -296.060 161.804
expression -20.3203 15.227 -1.334 0.209 -53.835 13.195
expression:C(dose)[T.1] 40.2362 36.706 1.096 0.296 -40.553 121.025
Omnibus: 3.879 Durbin-Watson: 0.808
Prob(Omnibus): 0.144 Jarque-Bera (JB): 1.930
Skew: -0.861 Prob(JB): 0.381
Kurtosis: 3.351 Cond. No. 52.8

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.488
Model: OLS Adj. R-squared: 0.403
Method: Least Squares F-statistic: 5.719
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0180
Time: 04:45:49 Log-Likelihood: -70.279
No. Observations: 15 AIC: 146.6
Df Residuals: 12 BIC: 148.7
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 107.9272 43.667 2.472 0.029 12.785 203.070
C(dose)[T.1] 45.6177 15.622 2.920 0.013 11.581 79.655
expression -13.3956 13.971 -0.959 0.357 -43.836 17.045
Omnibus: 1.870 Durbin-Watson: 0.925
Prob(Omnibus): 0.393 Jarque-Bera (JB): 1.379
Skew: -0.696 Prob(JB): 0.502
Kurtosis: 2.481 Cond. No. 19.1

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: 04:45:49 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: 0.124
Model: OLS Adj. R-squared: 0.057
Method: Least Squares F-statistic: 1.843
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.198
Time: 04:45:49 Log-Likelihood: -74.306
No. Observations: 15 AIC: 152.6
Df Residuals: 13 BIC: 154.0
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 160.3376 50.023 3.205 0.007 52.270 268.405
expression -23.1433 17.048 -1.358 0.198 -59.972 13.686
Omnibus: 4.039 Durbin-Watson: 1.890
Prob(Omnibus): 0.133 Jarque-Bera (JB): 1.615
Skew: 0.421 Prob(JB): 0.446
Kurtosis: 1.631 Cond. No. 17.2