LID SPN TRAP

1457426_at

1700048O20Rik RIKEN cDNA 1700048O20 gene

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
0.001 0.974 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.741
Model: OLS Adj. R-squared: 0.700
Method: Least Squares F-statistic: 18.08
Date: Thu, 21 Nov 2024 Prob (F-statistic): 8.55e-06
Time: 05:14:20 Log-Likelihood: -97.586
No. Observations: 23 AIC: 203.2
Df Residuals: 19 BIC: 207.7
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -81.0264 85.741 -0.945 0.357 -260.484 98.432
C(dose)[T.1] 425.6032 143.969 2.956 0.008 124.273 726.933
expression 17.9603 11.365 1.580 0.131 -5.827 41.747
expression:C(dose)[T.1] -49.1673 18.986 -2.590 0.018 -88.906 -9.429
Omnibus: 1.133 Durbin-Watson: 2.171
Prob(Omnibus): 0.568 Jarque-Bera (JB): 1.069
Skew: 0.421 Prob(JB): 0.586
Kurtosis: 2.361 Cond. No. 350.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.649
Model: OLS Adj. R-squared: 0.614
Method: Least Squares F-statistic: 18.50
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.83e-05
Time: 05:14:20 Log-Likelihood: -101.06
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 51.6270 77.952 0.662 0.515 -110.977 214.231
C(dose)[T.1] 53.3146 8.796 6.061 0.000 34.967 71.662
expression 0.3428 10.321 0.033 0.974 -21.187 21.873
Omnibus: 0.311 Durbin-Watson: 1.890
Prob(Omnibus): 0.856 Jarque-Bera (JB): 0.478
Skew: 0.050 Prob(JB): 0.787
Kurtosis: 2.301 Cond. No. 137.

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: 05:14:20 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: 0.004
Model: OLS Adj. R-squared: -0.043
Method: Least Squares F-statistic: 0.09360
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.763
Time: 05:14:20 Log-Likelihood: -113.05
No. Observations: 23 AIC: 230.1
Df Residuals: 21 BIC: 232.4
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 40.5883 128.097 0.317 0.754 -225.804 306.981
expression 5.1750 16.915 0.306 0.763 -30.001 40.351
Omnibus: 3.762 Durbin-Watson: 2.456
Prob(Omnibus): 0.152 Jarque-Bera (JB): 1.764
Skew: 0.348 Prob(JB): 0.414
Kurtosis: 1.836 Cond. No. 137.

CP101

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

F-statistic p-value df difference
2.900 0.114 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.566
Model: OLS Adj. R-squared: 0.447
Method: Least Squares F-statistic: 4.777
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0228
Time: 05:14:20 Log-Likelihood: -69.044
No. Observations: 15 AIC: 146.1
Df Residuals: 11 BIC: 148.9
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 186.7627 316.870 0.589 0.568 -510.664 884.189
C(dose)[T.1] 233.0036 364.809 0.639 0.536 -569.936 1035.943
expression -15.1813 40.288 -0.377 0.713 -103.856 73.493
expression:C(dose)[T.1] -22.8655 46.221 -0.495 0.631 -124.597 78.866
Omnibus: 2.405 Durbin-Watson: 1.394
Prob(Omnibus): 0.300 Jarque-Bera (JB): 0.997
Skew: -0.619 Prob(JB): 0.608
Kurtosis: 3.245 Cond. No. 602.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.556
Model: OLS Adj. R-squared: 0.482
Method: Least Squares F-statistic: 7.516
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00765
Time: 05:14:20 Log-Likelihood: -69.209
No. Observations: 15 AIC: 144.4
Df Residuals: 12 BIC: 146.5
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 323.3220 150.608 2.147 0.053 -4.826 651.470
C(dose)[T.1] 52.6795 14.272 3.691 0.003 21.583 83.776
expression -32.5540 19.115 -1.703 0.114 -74.202 9.094
Omnibus: 3.390 Durbin-Watson: 1.478
Prob(Omnibus): 0.184 Jarque-Bera (JB): 1.618
Skew: -0.790 Prob(JB): 0.445
Kurtosis: 3.309 Cond. No. 173.

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: 05:14:20 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: 0.052
Model: OLS Adj. R-squared: -0.021
Method: Least Squares F-statistic: 0.7141
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.413
Time: 05:14:21 Log-Likelihood: -74.899
No. Observations: 15 AIC: 153.8
Df Residuals: 13 BIC: 155.2
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 271.3681 210.521 1.289 0.220 -183.434 726.171
expression -22.4437 26.559 -0.845 0.413 -79.822 34.934
Omnibus: 0.009 Durbin-Watson: 1.878
Prob(Omnibus): 0.996 Jarque-Bera (JB): 0.173
Skew: -0.045 Prob(JB): 0.917
Kurtosis: 2.481 Cond. No. 171.