LID SPN TRAP

1454725_at

Tra2a transformer 2 alpha homolog (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
0.459 0.506 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.657
Model: OLS Adj. R-squared: 0.603
Method: Least Squares F-statistic: 12.13
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.000116
Time: 22:59:13 Log-Likelihood: -100.80
No. Observations: 23 AIC: 209.6
Df Residuals: 19 BIC: 214.1
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 205.6319 311.266 0.661 0.517 -445.856 857.120
C(dose)[T.1] 45.3973 446.894 0.102 0.920 -889.962 980.757
expression -14.9798 30.787 -0.487 0.632 -79.417 49.457
expression:C(dose)[T.1] 1.0764 43.737 0.025 0.981 -90.466 92.619
Omnibus: 0.191 Durbin-Watson: 1.834
Prob(Omnibus): 0.909 Jarque-Bera (JB): 0.400
Skew: 0.000 Prob(JB): 0.819
Kurtosis: 2.354 Cond. No. 1.34e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.657
Model: OLS Adj. R-squared: 0.623
Method: Least Squares F-statistic: 19.15
Date: Thu, 03 Apr 2025 Prob (F-statistic): 2.26e-05
Time: 22:59:13 Log-Likelihood: -100.80
No. Observations: 23 AIC: 207.6
Df Residuals: 20 BIC: 211.0
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 200.2406 215.537 0.929 0.364 -249.363 649.844
C(dose)[T.1] 56.3933 9.773 5.770 0.000 36.007 76.780
expression -14.4465 21.314 -0.678 0.506 -58.907 30.014
Omnibus: 0.182 Durbin-Watson: 1.833
Prob(Omnibus): 0.913 Jarque-Bera (JB): 0.393
Skew: -0.003 Prob(JB): 0.822
Kurtosis: 2.359 Cond. No. 514.

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: 22:59:13 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: 0.086
Model: OLS Adj. R-squared: 0.042
Method: Least Squares F-statistic: 1.971
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.175
Time: 22:59:13 Log-Likelihood: -112.07
No. Observations: 23 AIC: 228.1
Df Residuals: 21 BIC: 230.4
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -352.1094 307.646 -1.145 0.265 -991.894 287.675
expression 42.2959 30.125 1.404 0.175 -20.353 104.945
Omnibus: 0.891 Durbin-Watson: 2.610
Prob(Omnibus): 0.641 Jarque-Bera (JB): 0.864
Skew: 0.291 Prob(JB): 0.649
Kurtosis: 2.251 Cond. No. 460.

CP101

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

F-statistic p-value df difference
0.031 0.862 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.531
Model: OLS Adj. R-squared: 0.403
Method: Least Squares F-statistic: 4.145
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.0342
Time: 22:59:13 Log-Likelihood: -69.627
No. Observations: 15 AIC: 147.3
Df Residuals: 11 BIC: 150.1
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 901.1629 719.828 1.252 0.237 -683.168 2485.494
C(dose)[T.1] -1268.8805 961.724 -1.319 0.214 -3385.620 847.859
expression -84.1238 72.622 -1.158 0.271 -243.964 75.716
expression:C(dose)[T.1] 131.8681 96.049 1.373 0.197 -79.535 343.271
Omnibus: 2.339 Durbin-Watson: 1.195
Prob(Omnibus): 0.311 Jarque-Bera (JB): 1.705
Skew: -0.673 Prob(JB): 0.426
Kurtosis: 2.044 Cond. No. 1.77e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.450
Model: OLS Adj. R-squared: 0.359
Method: Least Squares F-statistic: 4.913
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.0276
Time: 22:59:13 Log-Likelihood: -70.813
No. Observations: 15 AIC: 147.6
Df Residuals: 12 BIC: 149.8
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 154.0296 488.241 0.315 0.758 -909.756 1217.815
C(dose)[T.1] 51.2386 19.483 2.630 0.022 8.790 93.687
expression -8.7380 49.250 -0.177 0.862 -116.044 98.568
Omnibus: 2.960 Durbin-Watson: 0.860
Prob(Omnibus): 0.228 Jarque-Bera (JB): 1.893
Skew: -0.863 Prob(JB): 0.388
Kurtosis: 2.774 Cond. No. 632.

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: 22:59:13 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: 0.133
Model: OLS Adj. R-squared: 0.067
Method: Least Squares F-statistic: 2.000
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.181
Time: 22:59:14 Log-Likelihood: -74.227
No. Observations: 15 AIC: 152.5
Df Residuals: 13 BIC: 153.9
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -586.5806 481.124 -1.219 0.244 -1625.985 452.824
expression 67.7845 47.933 1.414 0.181 -35.769 171.338
Omnibus: 0.660 Durbin-Watson: 1.142
Prob(Omnibus): 0.719 Jarque-Bera (JB): 0.513
Skew: -0.398 Prob(JB): 0.774
Kurtosis: 2.567 Cond. No. 516.