LID SPN TRAP

1450082_s_at

Etv5 ets variant gene 5

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
0.307 0.585 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.659
Model: OLS Adj. R-squared: 0.605
Method: Least Squares F-statistic: 12.24
Date: Wed, 29 Jan 2025 Prob (F-statistic): 0.000109
Time: 00:48:03 Log-Likelihood: -100.73
No. Observations: 23 AIC: 209.5
Df Residuals: 19 BIC: 214.0
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 203.6183 201.086 1.013 0.324 -217.260 624.497
C(dose)[T.1] -97.2326 290.646 -0.335 0.742 -705.562 511.097
expression -16.1271 21.695 -0.743 0.466 -61.535 29.281
expression:C(dose)[T.1] 16.2579 32.095 0.507 0.618 -50.918 83.434
Omnibus: 0.521 Durbin-Watson: 1.813
Prob(Omnibus): 0.771 Jarque-Bera (JB): 0.595
Skew: 0.092 Prob(JB): 0.742
Kurtosis: 2.233 Cond. No. 767.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.654
Model: OLS Adj. R-squared: 0.620
Method: Least Squares F-statistic: 18.93
Date: Wed, 29 Jan 2025 Prob (F-statistic): 2.43e-05
Time: 00:48:03 Log-Likelihood: -100.89
No. Observations: 23 AIC: 207.8
Df Residuals: 20 BIC: 211.2
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 134.7962 145.465 0.927 0.365 -168.639 438.231
C(dose)[T.1] 49.8924 10.693 4.666 0.000 27.587 72.198
expression -8.6986 15.688 -0.554 0.585 -41.423 24.026
Omnibus: 0.288 Durbin-Watson: 1.854
Prob(Omnibus): 0.866 Jarque-Bera (JB): 0.466
Skew: 0.135 Prob(JB): 0.792
Kurtosis: 2.357 Cond. No. 308.

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: Wed, 29 Jan 2025 Prob (F-statistic): 3.51e-06
Time: 00:48:03 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: 0.278
Model: OLS Adj. R-squared: 0.244
Method: Least Squares F-statistic: 8.092
Date: Wed, 29 Jan 2025 Prob (F-statistic): 0.00971
Time: 00:48:03 Log-Likelihood: -109.36
No. Observations: 23 AIC: 222.7
Df Residuals: 21 BIC: 225.0
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 544.5945 163.540 3.330 0.003 204.495 884.694
expression -51.2255 18.008 -2.845 0.010 -88.675 -13.776
Omnibus: 1.176 Durbin-Watson: 2.557
Prob(Omnibus): 0.555 Jarque-Bera (JB): 1.101
Skew: 0.432 Prob(JB): 0.577
Kurtosis: 2.367 Cond. No. 245.

CP101

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

F-statistic p-value df difference
1.229 0.289 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.515
Model: OLS Adj. R-squared: 0.383
Method: Least Squares F-statistic: 3.891
Date: Wed, 29 Jan 2025 Prob (F-statistic): 0.0405
Time: 00:48:03 Log-Likelihood: -69.876
No. Observations: 15 AIC: 147.8
Df Residuals: 11 BIC: 150.6
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 563.3661 413.642 1.362 0.200 -347.053 1473.785
C(dose)[T.1] -327.0663 642.631 -0.509 0.621 -1741.488 1087.355
expression -55.4417 46.225 -1.199 0.256 -157.181 46.298
expression:C(dose)[T.1] 41.9355 72.222 0.581 0.573 -117.024 200.895
Omnibus: 1.410 Durbin-Watson: 0.986
Prob(Omnibus): 0.494 Jarque-Bera (JB): 1.095
Skew: -0.599 Prob(JB): 0.578
Kurtosis: 2.437 Cond. No. 962.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.500
Model: OLS Adj. R-squared: 0.417
Method: Least Squares F-statistic: 5.999
Date: Wed, 29 Jan 2025 Prob (F-statistic): 0.0156
Time: 00:48:03 Log-Likelihood: -70.102
No. Observations: 15 AIC: 146.2
Df Residuals: 12 BIC: 148.3
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 409.6988 308.997 1.326 0.210 -263.547 1082.945
C(dose)[T.1] 45.9655 15.272 3.010 0.011 12.691 79.240
expression -38.2630 34.522 -1.108 0.289 -113.479 36.953
Omnibus: 1.728 Durbin-Watson: 0.898
Prob(Omnibus): 0.421 Jarque-Bera (JB): 1.318
Skew: -0.559 Prob(JB): 0.517
Kurtosis: 2.072 Cond. No. 373.

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: Wed, 29 Jan 2025 Prob (F-statistic): 0.00629
Time: 00:48:03 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: 0.122
Model: OLS Adj. R-squared: 0.055
Method: Least Squares F-statistic: 1.814
Date: Wed, 29 Jan 2025 Prob (F-statistic): 0.201
Time: 00:48:03 Log-Likelihood: -74.320
No. Observations: 15 AIC: 152.6
Df Residuals: 13 BIC: 154.1
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 610.7277 383.983 1.591 0.136 -218.817 1440.272
expression -58.0956 43.130 -1.347 0.201 -151.272 35.081
Omnibus: 5.524 Durbin-Watson: 1.313
Prob(Omnibus): 0.063 Jarque-Bera (JB): 1.791
Skew: 0.409 Prob(JB): 0.408
Kurtosis: 1.518 Cond. No. 364.