LID SPN TRAP

1422711_a_at

Pnck pregnancy upregulated non-ubiquitously expressed CaM kinase

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
0.047 0.831 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.656
Model: OLS Adj. R-squared: 0.602
Method: Least Squares F-statistic: 12.08
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.000119
Time: 04:32:26 Log-Likelihood: -100.83
No. Observations: 23 AIC: 209.7
Df Residuals: 19 BIC: 214.2
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -26.1874 170.550 -0.154 0.880 -383.152 330.777
C(dose)[T.1] 247.7035 331.415 0.747 0.464 -445.957 941.364
expression 8.6522 18.343 0.472 0.643 -29.739 47.044
expression:C(dose)[T.1] -21.6145 37.154 -0.582 0.568 -99.379 56.150
Omnibus: 0.342 Durbin-Watson: 1.749
Prob(Omnibus): 0.843 Jarque-Bera (JB): 0.499
Skew: -0.083 Prob(JB): 0.779
Kurtosis: 2.298 Cond. No. 797.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.650
Model: OLS Adj. R-squared: 0.615
Method: Least Squares F-statistic: 18.56
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.77e-05
Time: 04:32:26 Log-Likelihood: -101.04
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 22.7637 145.873 0.156 0.878 -281.523 327.050
C(dose)[T.1] 55.0271 11.751 4.683 0.000 30.514 79.540
expression 3.3841 15.685 0.216 0.831 -29.335 36.103
Omnibus: 0.460 Durbin-Watson: 1.802
Prob(Omnibus): 0.794 Jarque-Bera (JB): 0.560
Skew: 0.056 Prob(JB): 0.756
Kurtosis: 2.244 Cond. No. 307.

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: 04:32:26 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: 0.266
Model: OLS Adj. R-squared: 0.231
Method: Least Squares F-statistic: 7.610
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0118
Time: 04:32:26 Log-Likelihood: -109.55
No. Observations: 23 AIC: 223.1
Df Residuals: 21 BIC: 225.4
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 492.3261 149.694 3.289 0.003 181.020 803.632
expression -45.5767 16.521 -2.759 0.012 -79.934 -11.219
Omnibus: 2.451 Durbin-Watson: 2.718
Prob(Omnibus): 0.294 Jarque-Bera (JB): 1.170
Skew: -0.032 Prob(JB): 0.557
Kurtosis: 1.897 Cond. No. 222.

CP101

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

F-statistic p-value df difference
1.687 0.218 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.608
Model: OLS Adj. R-squared: 0.501
Method: Least Squares F-statistic: 5.686
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0134
Time: 04:32:26 Log-Likelihood: -68.277
No. Observations: 15 AIC: 144.6
Df Residuals: 11 BIC: 147.4
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -831.6920 761.848 -1.092 0.298 -2508.509 845.125
C(dose)[T.1] 1310.5109 789.421 1.660 0.125 -426.994 3048.016
expression 105.8444 89.677 1.180 0.263 -91.533 303.222
expression:C(dose)[T.1] -148.7338 92.954 -1.600 0.138 -353.324 55.857
Omnibus: 2.582 Durbin-Watson: 1.077
Prob(Omnibus): 0.275 Jarque-Bera (JB): 1.208
Skew: -0.297 Prob(JB): 0.547
Kurtosis: 1.743 Cond. No. 1.57e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.517
Model: OLS Adj. R-squared: 0.436
Method: Least Squares F-statistic: 6.415
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0127
Time: 04:32:26 Log-Likelihood: -69.847
No. Observations: 15 AIC: 145.7
Df Residuals: 12 BIC: 147.8
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 344.2434 213.401 1.613 0.133 -120.718 809.205
C(dose)[T.1] 47.5708 14.791 3.216 0.007 15.344 79.797
expression -32.5866 25.090 -1.299 0.218 -87.252 22.079
Omnibus: 2.317 Durbin-Watson: 0.789
Prob(Omnibus): 0.314 Jarque-Bera (JB): 1.770
Skew: -0.730 Prob(JB): 0.413
Kurtosis: 2.164 Cond. No. 250.

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: 04:32:26 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: 0.100
Model: OLS Adj. R-squared: 0.031
Method: Least Squares F-statistic: 1.446
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.251
Time: 04:32:26 Log-Likelihood: -74.509
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 427.4385 277.711 1.539 0.148 -172.520 1027.397
expression -39.4151 32.775 -1.203 0.251 -110.221 31.391
Omnibus: 0.231 Durbin-Watson: 1.525
Prob(Omnibus): 0.891 Jarque-Bera (JB): 0.169
Skew: -0.196 Prob(JB): 0.919
Kurtosis: 2.658 Cond. No. 248.