LID SPN TRAP

1455758_at

Prkcc protein kinase C, gamma

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
4.108 0.056 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.747
Model: OLS Adj. R-squared: 0.707
Method: Least Squares F-statistic: 18.71
Date: Thu, 21 Nov 2024 Prob (F-statistic): 6.75e-06
Time: 04:47:14 Log-Likelihood: -97.295
No. Observations: 23 AIC: 202.6
Df Residuals: 19 BIC: 207.1
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 381.8839 318.148 1.200 0.245 -284.006 1047.774
C(dose)[T.1] 1144.0676 648.391 1.764 0.094 -213.031 2501.166
expression -28.6475 27.811 -1.030 0.316 -86.856 29.561
expression:C(dose)[T.1] -97.0877 57.284 -1.695 0.106 -216.984 22.808
Omnibus: 0.676 Durbin-Watson: 2.046
Prob(Omnibus): 0.713 Jarque-Bera (JB): 0.675
Skew: -0.121 Prob(JB): 0.714
Kurtosis: 2.196 Cond. No. 2.27e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.709
Model: OLS Adj. R-squared: 0.680
Method: Least Squares F-statistic: 24.35
Date: Thu, 21 Nov 2024 Prob (F-statistic): 4.38e-06
Time: 04:47:14 Log-Likelihood: -98.915
No. Observations: 23 AIC: 203.8
Df Residuals: 20 BIC: 207.2
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 643.6313 290.880 2.213 0.039 36.867 1250.396
C(dose)[T.1] 45.2309 8.933 5.063 0.000 26.596 63.865
expression -51.5311 25.426 -2.027 0.056 -104.569 1.507
Omnibus: 1.286 Durbin-Watson: 2.235
Prob(Omnibus): 0.526 Jarque-Bera (JB): 1.003
Skew: -0.258 Prob(JB): 0.606
Kurtosis: 2.117 Cond. No. 836.

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: 04:47:14 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: 0.336
Model: OLS Adj. R-squared: 0.304
Method: Least Squares F-statistic: 10.61
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00377
Time: 04:47:14 Log-Likelihood: -108.40
No. Observations: 23 AIC: 220.8
Df Residuals: 21 BIC: 223.1
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 1320.2144 380.877 3.466 0.002 528.137 2112.292
expression -109.1701 33.515 -3.257 0.004 -178.869 -39.472
Omnibus: 1.148 Durbin-Watson: 2.707
Prob(Omnibus): 0.563 Jarque-Bera (JB): 0.999
Skew: -0.463 Prob(JB): 0.607
Kurtosis: 2.570 Cond. No. 742.

CP101

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

F-statistic p-value df difference
0.641 0.439 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.480
Model: OLS Adj. R-squared: 0.338
Method: Least Squares F-statistic: 3.387
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0577
Time: 04:47:14 Log-Likelihood: -70.393
No. Observations: 15 AIC: 148.8
Df Residuals: 11 BIC: 151.6
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 344.6373 373.903 0.922 0.376 -478.318 1167.593
C(dose)[T.1] -96.7311 538.513 -0.180 0.861 -1281.990 1088.528
expression -26.9589 36.345 -0.742 0.474 -106.953 53.036
expression:C(dose)[T.1] 14.1951 52.341 0.271 0.791 -101.006 129.396
Omnibus: 2.171 Durbin-Watson: 0.756
Prob(Omnibus): 0.338 Jarque-Bera (JB): 1.545
Skew: -0.752 Prob(JB): 0.462
Kurtosis: 2.542 Cond. No. 926.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.477
Model: OLS Adj. R-squared: 0.390
Method: Least Squares F-statistic: 5.466
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0205
Time: 04:47:14 Log-Likelihood: -70.443
No. Observations: 15 AIC: 146.9
Df Residuals: 12 BIC: 149.0
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 274.2563 258.582 1.061 0.310 -289.145 837.657
C(dose)[T.1] 49.2536 15.336 3.212 0.007 15.840 82.667
expression -20.1142 25.124 -0.801 0.439 -74.854 34.626
Omnibus: 2.387 Durbin-Watson: 0.758
Prob(Omnibus): 0.303 Jarque-Bera (JB): 1.689
Skew: -0.791 Prob(JB): 0.430
Kurtosis: 2.554 Cond. No. 351.

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: 04:47:14 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: 0.027
Model: OLS Adj. R-squared: -0.048
Method: Least Squares F-statistic: 0.3596
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.559
Time: 04:47:14 Log-Likelihood: -75.095
No. Observations: 15 AIC: 154.2
Df Residuals: 13 BIC: 155.6
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 296.6640 338.663 0.876 0.397 -434.973 1028.301
expression -19.7388 32.916 -0.600 0.559 -90.850 51.372
Omnibus: 2.309 Durbin-Watson: 1.688
Prob(Omnibus): 0.315 Jarque-Bera (JB): 1.038
Skew: 0.141 Prob(JB): 0.595
Kurtosis: 1.742 Cond. No. 351.