LID SPN TRAP

1453187_at

Ociad2 OCIA domain containing 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
0.187 0.670 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.684
Model: OLS Adj. R-squared: 0.635
Method: Least Squares F-statistic: 13.73
Date: Thu, 21 Nov 2024 Prob (F-statistic): 5.33e-05
Time: 05:22:45 Log-Likelihood: -99.842
No. Observations: 23 AIC: 207.7
Df Residuals: 19 BIC: 212.2
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -602.4686 583.367 -1.033 0.315 -1823.469 618.532
C(dose)[T.1] 1566.6360 1092.200 1.434 0.168 -719.365 3852.637
expression 58.5407 52.003 1.126 0.274 -50.302 167.384
expression:C(dose)[T.1] -133.2392 95.849 -1.390 0.181 -333.854 67.376
Omnibus: 0.077 Durbin-Watson: 1.774
Prob(Omnibus): 0.962 Jarque-Bera (JB): 0.050
Skew: 0.022 Prob(JB): 0.975
Kurtosis: 2.777 Cond. No. 3.50e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.652
Model: OLS Adj. R-squared: 0.618
Method: Least Squares F-statistic: 18.76
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.58e-05
Time: 05:22:45 Log-Likelihood: -100.96
No. Observations: 23 AIC: 207.9
Df Residuals: 20 BIC: 211.3
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -162.5220 501.346 -0.324 0.749 -1208.311 883.267
C(dose)[T.1] 48.5010 14.189 3.418 0.003 18.903 78.099
expression 19.3208 44.690 0.432 0.670 -73.901 112.543
Omnibus: 0.373 Durbin-Watson: 1.939
Prob(Omnibus): 0.830 Jarque-Bera (JB): 0.521
Skew: 0.123 Prob(JB): 0.770
Kurtosis: 2.304 Cond. No. 1.32e+03

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: 05:22:45 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: 0.449
Model: OLS Adj. R-squared: 0.423
Method: Least Squares F-statistic: 17.12
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.000467
Time: 05:22:45 Log-Likelihood: -106.25
No. Observations: 23 AIC: 216.5
Df Residuals: 21 BIC: 218.8
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -1504.6754 382.905 -3.930 0.001 -2300.970 -708.381
expression 139.7524 33.771 4.138 0.000 69.522 209.983
Omnibus: 3.674 Durbin-Watson: 2.092
Prob(Omnibus): 0.159 Jarque-Bera (JB): 2.496
Skew: 0.805 Prob(JB): 0.287
Kurtosis: 3.096 Cond. No. 817.

CP101

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

F-statistic p-value df difference
0.554 0.471 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.524
Model: OLS Adj. R-squared: 0.395
Method: Least Squares F-statistic: 4.041
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0366
Time: 05:22:45 Log-Likelihood: -69.728
No. Observations: 15 AIC: 147.5
Df Residuals: 11 BIC: 150.3
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -859.9142 708.608 -1.214 0.250 -2419.550 699.721
C(dose)[T.1] 912.2343 792.155 1.152 0.274 -831.287 2655.755
expression 87.8364 67.110 1.309 0.217 -59.871 235.544
expression:C(dose)[T.1] -81.7074 75.112 -1.088 0.300 -247.027 83.613
Omnibus: 2.280 Durbin-Watson: 1.169
Prob(Omnibus): 0.320 Jarque-Bera (JB): 1.531
Skew: -0.762 Prob(JB): 0.465
Kurtosis: 2.647 Cond. No. 1.67e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.473
Model: OLS Adj. R-squared: 0.385
Method: Least Squares F-statistic: 5.388
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0214
Time: 05:22:45 Log-Likelihood: -70.494
No. Observations: 15 AIC: 147.0
Df Residuals: 12 BIC: 149.1
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -171.2883 320.836 -0.534 0.603 -870.330 527.754
C(dose)[T.1] 50.6832 15.517 3.266 0.007 16.874 84.492
expression 22.6109 30.370 0.745 0.471 -43.561 88.782
Omnibus: 2.640 Durbin-Watson: 0.807
Prob(Omnibus): 0.267 Jarque-Bera (JB): 1.991
Skew: -0.784 Prob(JB): 0.370
Kurtosis: 2.146 Cond. No. 444.

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: 05:22:45 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: 0.005
Model: OLS Adj. R-squared: -0.072
Method: Least Squares F-statistic: 0.06127
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.808
Time: 05:22:45 Log-Likelihood: -75.265
No. Observations: 15 AIC: 154.5
Df Residuals: 13 BIC: 155.9
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -9.9243 418.611 -0.024 0.981 -914.278 894.430
expression 9.8447 39.771 0.248 0.808 -76.075 95.764
Omnibus: 0.972 Durbin-Watson: 1.668
Prob(Omnibus): 0.615 Jarque-Bera (JB): 0.713
Skew: 0.106 Prob(JB): 0.700
Kurtosis: 1.953 Cond. No. 439.