LID SPN TRAP

1457262_at

Smg1 SMG1 homolog, phosphatidylinositol 3-kinase-related kinase (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
0.004 0.950 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.750
Model: OLS Adj. R-squared: 0.711
Method: Least Squares F-statistic: 19.02
Date: Thu, 21 Nov 2024 Prob (F-statistic): 6.02e-06
Time: 04:43:20 Log-Likelihood: -97.153
No. Observations: 23 AIC: 202.3
Df Residuals: 19 BIC: 206.8
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -49.0695 66.049 -0.743 0.467 -187.313 89.174
C(dose)[T.1] 349.8314 107.370 3.258 0.004 125.104 574.559
expression 15.3784 9.804 1.569 0.133 -5.141 35.898
expression:C(dose)[T.1] -46.2847 16.694 -2.773 0.012 -81.226 -11.344
Omnibus: 0.459 Durbin-Watson: 1.541
Prob(Omnibus): 0.795 Jarque-Bera (JB): 0.358
Skew: 0.275 Prob(JB): 0.836
Kurtosis: 2.732 Cond. No. 229.

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: 18.50
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.83e-05
Time: 04:43:20 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 58.1327 61.856 0.940 0.359 -70.897 187.163
C(dose)[T.1] 53.0659 9.746 5.445 0.000 32.735 73.396
expression -0.5843 9.166 -0.064 0.950 -19.705 18.536
Omnibus: 0.355 Durbin-Watson: 1.890
Prob(Omnibus): 0.838 Jarque-Bera (JB): 0.505
Skew: 0.075 Prob(JB): 0.777
Kurtosis: 2.290 Cond. No. 94.6

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: 04:43:20 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: 0.129
Model: OLS Adj. R-squared: 0.088
Method: Least Squares F-statistic: 3.112
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0923
Time: 04:43:20 Log-Likelihood: -111.52
No. Observations: 23 AIC: 227.0
Df Residuals: 21 BIC: 229.3
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 224.9676 82.618 2.723 0.013 53.155 396.780
expression -22.3675 12.680 -1.764 0.092 -48.737 4.002
Omnibus: 2.466 Durbin-Watson: 2.436
Prob(Omnibus): 0.291 Jarque-Bera (JB): 1.177
Skew: -0.049 Prob(JB): 0.555
Kurtosis: 1.896 Cond. No. 81.8

CP101

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

F-statistic p-value df difference
3.015 0.108 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.560
Model: OLS Adj. R-squared: 0.440
Method: Least Squares F-statistic: 4.674
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0243
Time: 04:43:20 Log-Likelihood: -69.136
No. Observations: 15 AIC: 146.3
Df Residuals: 11 BIC: 149.1
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 212.5655 104.935 2.026 0.068 -18.394 443.525
C(dose)[T.1] 83.1189 220.011 0.378 0.713 -401.122 567.360
expression -19.6533 14.135 -1.390 0.192 -50.764 11.458
expression:C(dose)[T.1] -4.5055 29.642 -0.152 0.882 -69.748 60.737
Omnibus: 4.174 Durbin-Watson: 0.770
Prob(Omnibus): 0.124 Jarque-Bera (JB): 2.304
Skew: -0.954 Prob(JB): 0.316
Kurtosis: 3.211 Cond. No. 272.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.559
Model: OLS Adj. R-squared: 0.486
Method: Least Squares F-statistic: 7.620
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00731
Time: 04:43:20 Log-Likelihood: -69.152
No. Observations: 15 AIC: 144.3
Df Residuals: 12 BIC: 146.4
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 220.1313 88.537 2.486 0.029 27.225 413.038
C(dose)[T.1] 49.7524 14.074 3.535 0.004 19.087 80.418
expression -20.6778 11.908 -1.736 0.108 -46.623 5.268
Omnibus: 4.019 Durbin-Watson: 0.790
Prob(Omnibus): 0.134 Jarque-Bera (JB): 2.238
Skew: -0.943 Prob(JB): 0.327
Kurtosis: 3.166 Cond. No. 95.5

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: 04:43:20 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: 0.101
Model: OLS Adj. R-squared: 0.032
Method: Least Squares F-statistic: 1.456
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.249
Time: 04:43:20 Log-Likelihood: -74.504
No. Observations: 15 AIC: 153.0
Df Residuals: 13 BIC: 154.4
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 239.5801 121.300 1.975 0.070 -22.473 501.633
expression -19.7201 16.342 -1.207 0.249 -55.025 15.584
Omnibus: 3.559 Durbin-Watson: 1.873
Prob(Omnibus): 0.169 Jarque-Bera (JB): 1.332
Skew: 0.257 Prob(JB): 0.514
Kurtosis: 1.634 Cond. No. 95.1