LID SPN TRAP

1418300_a_at

Mknk2 MAP kinase-interacting serine/threonine kinase 2

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
0.086 0.772 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.651
Model: OLS Adj. R-squared: 0.596
Method: Least Squares F-statistic: 11.83
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.000135
Time: 05:01:06 Log-Likelihood: -100.99
No. Observations: 23 AIC: 210.0
Df Residuals: 19 BIC: 214.5
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 97.1923 195.699 0.497 0.625 -312.410 506.795
C(dose)[T.1] 195.9732 720.333 0.272 0.789 -1311.700 1703.647
expression -3.9715 18.073 -0.220 0.828 -41.798 33.855
expression:C(dose)[T.1] -12.3987 63.751 -0.194 0.848 -145.831 121.034
Omnibus: 1.256 Durbin-Watson: 1.931
Prob(Omnibus): 0.534 Jarque-Bera (JB): 0.895
Skew: 0.130 Prob(JB): 0.639
Kurtosis: 2.069 Cond. No. 2.06e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.651
Model: OLS Adj. R-squared: 0.616
Method: Least Squares F-statistic: 18.62
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.71e-05
Time: 05:01:07 Log-Likelihood: -101.01
No. Observations: 23 AIC: 208.0
Df Residuals: 20 BIC: 211.4
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 107.9766 183.109 0.590 0.562 -273.981 489.935
C(dose)[T.1] 55.8999 12.356 4.524 0.000 30.126 81.674
expression -4.9680 16.909 -0.294 0.772 -40.240 30.304
Omnibus: 0.692 Durbin-Watson: 1.952
Prob(Omnibus): 0.707 Jarque-Bera (JB): 0.669
Skew: 0.072 Prob(JB): 0.716
Kurtosis: 2.177 Cond. No. 469.

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: 05:01:07 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: 0.293
Model: OLS Adj. R-squared: 0.259
Method: Least Squares F-statistic: 8.701
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00765
Time: 05:01:07 Log-Likelihood: -109.12
No. Observations: 23 AIC: 222.2
Df Residuals: 21 BIC: 224.5
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -463.1243 184.133 -2.515 0.020 -846.050 -80.199
expression 49.0385 16.625 2.950 0.008 14.465 83.612
Omnibus: 3.022 Durbin-Watson: 1.899
Prob(Omnibus): 0.221 Jarque-Bera (JB): 1.284
Skew: 0.010 Prob(JB): 0.526
Kurtosis: 1.843 Cond. No. 339.

CP101

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

F-statistic p-value df difference
0.081 0.781 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.483
Model: OLS Adj. R-squared: 0.342
Method: Least Squares F-statistic: 3.420
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0563
Time: 05:01:07 Log-Likelihood: -70.358
No. Observations: 15 AIC: 148.7
Df Residuals: 11 BIC: 151.5
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 204.8055 456.559 0.449 0.662 -800.073 1209.684
C(dose)[T.1] -524.9356 715.349 -0.734 0.478 -2099.408 1049.537
expression -12.6987 42.189 -0.301 0.769 -105.557 80.159
expression:C(dose)[T.1] 52.4982 65.554 0.801 0.440 -91.785 196.781
Omnibus: 2.718 Durbin-Watson: 0.826
Prob(Omnibus): 0.257 Jarque-Bera (JB): 1.780
Skew: -0.648 Prob(JB): 0.411
Kurtosis: 1.919 Cond. No. 1.27e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.452
Model: OLS Adj. R-squared: 0.361
Method: Least Squares F-statistic: 4.958
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0269
Time: 05:01:07 Log-Likelihood: -70.783
No. Observations: 15 AIC: 147.6
Df Residuals: 12 BIC: 149.7
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -30.4308 344.257 -0.088 0.931 -780.503 719.641
C(dose)[T.1] 47.7876 16.450 2.905 0.013 11.946 83.630
expression 9.0458 31.805 0.284 0.781 -60.250 78.342
Omnibus: 2.244 Durbin-Watson: 0.900
Prob(Omnibus): 0.326 Jarque-Bera (JB): 1.697
Skew: -0.764 Prob(JB): 0.428
Kurtosis: 2.386 Cond. No. 484.

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: 05:01:07 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: 0.067
Model: OLS Adj. R-squared: -0.004
Method: Least Squares F-statistic: 0.9397
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.350
Time: 05:01:07 Log-Likelihood: -74.777
No. Observations: 15 AIC: 153.6
Df Residuals: 13 BIC: 155.0
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -308.2057 414.673 -0.743 0.471 -1204.052 587.641
expression 36.8649 38.028 0.969 0.350 -45.291 119.020
Omnibus: 0.317 Durbin-Watson: 1.582
Prob(Omnibus): 0.854 Jarque-Bera (JB): 0.461
Skew: -0.072 Prob(JB): 0.794
Kurtosis: 2.153 Cond. No. 465.