LID SPN TRAP

1448842_at

Cdo1 cysteine dioxygenase 1, cytosolic

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
2.110 0.162 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.719
Model: OLS Adj. R-squared: 0.675
Method: Least Squares F-statistic: 16.24
Date: Thu, 21 Nov 2024 Prob (F-statistic): 1.78e-05
Time: 05:26:50 Log-Likelihood: -98.487
No. Observations: 23 AIC: 205.0
Df Residuals: 19 BIC: 209.5
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 42.0736 462.370 0.091 0.928 -925.679 1009.826
C(dose)[T.1] -1015.8249 677.455 -1.499 0.150 -2433.754 402.105
expression 1.0945 41.699 0.026 0.979 -86.183 88.372
expression:C(dose)[T.1] 96.8965 61.253 1.582 0.130 -31.308 225.101
Omnibus: 0.272 Durbin-Watson: 2.263
Prob(Omnibus): 0.873 Jarque-Bera (JB): 0.397
Skew: 0.214 Prob(JB): 0.820
Kurtosis: 2.519 Cond. No. 2.40e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.683
Model: OLS Adj. R-squared: 0.651
Method: Least Squares F-statistic: 21.50
Date: Thu, 21 Nov 2024 Prob (F-statistic): 1.04e-05
Time: 05:26:50 Log-Likelihood: -99.909
No. Observations: 23 AIC: 205.8
Df Residuals: 20 BIC: 209.2
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -455.8218 351.197 -1.298 0.209 -1188.407 276.763
C(dose)[T.1] 55.7618 8.506 6.555 0.000 38.018 73.506
expression 46.0010 31.671 1.452 0.162 -20.064 112.066
Omnibus: 2.714 Durbin-Watson: 2.349
Prob(Omnibus): 0.257 Jarque-Bera (JB): 1.440
Skew: 0.287 Prob(JB): 0.487
Kurtosis: 1.916 Cond. No. 941.

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: 05:26:50 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: 0.000
Model: OLS Adj. R-squared: -0.047
Method: Least Squares F-statistic: 0.009558
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.923
Time: 05:26:50 Log-Likelihood: -113.10
No. Observations: 23 AIC: 230.2
Df Residuals: 21 BIC: 232.5
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 21.5579 594.938 0.036 0.971 -1215.683 1258.799
expression 5.2575 53.777 0.098 0.923 -106.579 117.094
Omnibus: 3.441 Durbin-Watson: 2.517
Prob(Omnibus): 0.179 Jarque-Bera (JB): 1.581
Skew: 0.279 Prob(JB): 0.454
Kurtosis: 1.843 Cond. No. 920.

CP101

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

F-statistic p-value df difference
0.214 0.652 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.475
Model: OLS Adj. R-squared: 0.332
Method: Least Squares F-statistic: 3.322
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0605
Time: 05:26:50 Log-Likelihood: -70.462
No. Observations: 15 AIC: 148.9
Df Residuals: 11 BIC: 151.8
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -449.9515 711.094 -0.633 0.540 -2015.058 1115.155
C(dose)[T.1] 712.1414 1122.370 0.634 0.539 -1758.177 3182.460
expression 50.3676 69.216 0.728 0.482 -101.977 202.712
expression:C(dose)[T.1] -64.1964 107.682 -0.596 0.563 -301.203 172.810
Omnibus: 3.805 Durbin-Watson: 1.027
Prob(Omnibus): 0.149 Jarque-Bera (JB): 2.329
Skew: -0.965 Prob(JB): 0.312
Kurtosis: 2.950 Cond. No. 1.89e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.458
Model: OLS Adj. R-squared: 0.368
Method: Least Squares F-statistic: 5.079
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0252
Time: 05:26:50 Log-Likelihood: -70.701
No. Observations: 15 AIC: 147.4
Df Residuals: 12 BIC: 149.5
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -177.4916 529.949 -0.335 0.743 -1332.151 977.167
C(dose)[T.1] 43.1380 20.376 2.117 0.056 -1.257 87.533
expression 23.8433 51.579 0.462 0.652 -88.538 136.225
Omnibus: 2.325 Durbin-Watson: 0.924
Prob(Omnibus): 0.313 Jarque-Bera (JB): 1.754
Skew: -0.780 Prob(JB): 0.416
Kurtosis: 2.388 Cond. No. 717.

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: 05:26:50 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: 0.256
Model: OLS Adj. R-squared: 0.199
Method: Least Squares F-statistic: 4.476
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0542
Time: 05:26:50 Log-Likelihood: -73.081
No. Observations: 15 AIC: 150.2
Df Residuals: 13 BIC: 151.6
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -885.5065 462.902 -1.913 0.078 -1885.545 114.532
expression 94.0825 44.469 2.116 0.054 -1.988 190.153
Omnibus: 1.307 Durbin-Watson: 1.742
Prob(Omnibus): 0.520 Jarque-Bera (JB): 0.799
Skew: 0.083 Prob(JB): 0.671
Kurtosis: 1.881 Cond. No. 555.