LID SPN TRAP

1425671_at

Homer1 homer 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
0.458 0.506 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.693
Model: OLS Adj. R-squared: 0.644
Method: Least Squares F-statistic: 14.26
Date: Thu, 21 Nov 2024 Prob (F-statistic): 4.18e-05
Time: 04:35:25 Log-Likelihood: -99.542
No. Observations: 23 AIC: 207.1
Df Residuals: 19 BIC: 211.6
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -5.7426 441.688 -0.013 0.990 -930.206 918.721
C(dose)[T.1] 1388.4089 897.037 1.548 0.138 -489.112 3265.929
expression 4.9000 36.097 0.136 0.893 -70.653 80.453
expression:C(dose)[T.1] -107.3984 72.399 -1.483 0.154 -258.931 44.134
Omnibus: 0.585 Durbin-Watson: 1.852
Prob(Omnibus): 0.746 Jarque-Bera (JB): 0.033
Skew: 0.052 Prob(JB): 0.984
Kurtosis: 3.153 Cond. No. 3.12e+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, 21 Nov 2024 Prob (F-statistic): 2.26e-05
Time: 04:35:25 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 320.9098 394.207 0.814 0.425 -501.392 1143.212
C(dose)[T.1] 57.8154 10.908 5.300 0.000 35.061 80.570
expression -21.7983 32.216 -0.677 0.506 -89.000 45.403
Omnibus: 0.715 Durbin-Watson: 1.857
Prob(Omnibus): 0.699 Jarque-Bera (JB): 0.672
Skew: -0.036 Prob(JB): 0.715
Kurtosis: 2.166 Cond. No. 1.13e+03

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: 04:35:25 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: 0.175
Model: OLS Adj. R-squared: 0.136
Method: Least Squares F-statistic: 4.455
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0470
Time: 04:35:25 Log-Likelihood: -110.89
No. Observations: 23 AIC: 225.8
Df Residuals: 21 BIC: 228.1
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -929.1376 477.996 -1.944 0.065 -1923.185 64.910
expression 81.7999 38.753 2.111 0.047 1.208 162.392
Omnibus: 1.740 Durbin-Watson: 2.235
Prob(Omnibus): 0.419 Jarque-Bera (JB): 1.487
Skew: 0.497 Prob(JB): 0.475
Kurtosis: 2.249 Cond. No. 905.

CP101

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

F-statistic p-value df difference
0.534 0.479 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.526
Model: OLS Adj. R-squared: 0.396
Method: Least Squares F-statistic: 4.064
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0360
Time: 04:35:25 Log-Likelihood: -69.705
No. Observations: 15 AIC: 147.4
Df Residuals: 11 BIC: 150.2
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 492.8971 337.742 1.459 0.172 -250.468 1236.262
C(dose)[T.1] -575.4686 562.827 -1.022 0.329 -1814.243 663.306
expression -38.5660 30.597 -1.260 0.234 -105.910 28.779
expression:C(dose)[T.1] 56.4652 50.715 1.113 0.289 -55.158 168.089
Omnibus: 1.422 Durbin-Watson: 1.050
Prob(Omnibus): 0.491 Jarque-Bera (JB): 0.934
Skew: -0.586 Prob(JB): 0.627
Kurtosis: 2.655 Cond. No. 1.04e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.472
Model: OLS Adj. R-squared: 0.384
Method: Least Squares F-statistic: 5.369
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0216
Time: 04:35:25 Log-Likelihood: -70.506
No. Observations: 15 AIC: 147.0
Df Residuals: 12 BIC: 149.1
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 266.1519 272.110 0.978 0.347 -326.724 859.028
C(dose)[T.1] 50.9353 15.583 3.269 0.007 16.982 84.888
expression -18.0130 24.644 -0.731 0.479 -71.707 35.681
Omnibus: 3.942 Durbin-Watson: 0.736
Prob(Omnibus): 0.139 Jarque-Bera (JB): 2.427
Skew: -0.985 Prob(JB): 0.297
Kurtosis: 2.957 Cond. No. 396.

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: 04:35:25 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: 0.002
Model: OLS Adj. R-squared: -0.074
Method: Least Squares F-statistic: 0.03157
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.862
Time: 04:35:25 Log-Likelihood: -75.282
No. Observations: 15 AIC: 154.6
Df Residuals: 13 BIC: 156.0
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 157.0216 356.727 0.440 0.667 -613.639 927.683
expression -5.7160 32.172 -0.178 0.862 -75.219 63.787
Omnibus: 1.022 Durbin-Watson: 1.660
Prob(Omnibus): 0.600 Jarque-Bera (JB): 0.725
Skew: 0.094 Prob(JB): 0.696
Kurtosis: 1.940 Cond. No. 393.