LID SPN TRAP

1428545_at

0610007L01Rik RIKEN cDNA 0610007L01 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
0.005 0.944 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: 0.601
Method: Least Squares F-statistic: 12.06
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.000119
Time: 06:23:20 Log-Likelihood: -100.84
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 97.2238 98.047 0.992 0.334 -107.992 302.439
C(dose)[T.1] -39.0797 153.188 -0.255 0.801 -359.706 281.547
expression -6.6079 15.032 -0.440 0.665 -38.070 24.854
expression:C(dose)[T.1] 14.2226 23.540 0.604 0.553 -35.047 63.492
Omnibus: 0.663 Durbin-Watson: 1.874
Prob(Omnibus): 0.718 Jarque-Bera (JB): 0.651
Skew: -0.040 Prob(JB): 0.722
Kurtosis: 2.180 Cond. No. 286.

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: 06:23:20 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 59.4693 74.347 0.800 0.433 -95.615 214.553
C(dose)[T.1] 53.3193 8.772 6.078 0.000 35.020 71.618
expression -0.8082 11.383 -0.071 0.944 -24.552 22.936
Omnibus: 0.343 Durbin-Watson: 1.873
Prob(Omnibus): 0.842 Jarque-Bera (JB): 0.497
Skew: 0.051 Prob(JB): 0.780
Kurtosis: 2.287 Cond. No. 113.

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: 06:23:20 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: 0.001
Model: OLS Adj. R-squared: -0.047
Method: Least Squares F-statistic: 0.02217
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.883
Time: 06:23:20 Log-Likelihood: -113.09
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 97.8496 121.983 0.802 0.431 -155.829 351.528
expression -2.7899 18.736 -0.149 0.883 -41.754 36.174
Omnibus: 3.112 Durbin-Watson: 2.494
Prob(Omnibus): 0.211 Jarque-Bera (JB): 1.540
Skew: 0.295 Prob(JB): 0.463
Kurtosis: 1.878 Cond. No. 113.

CP101

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

F-statistic p-value df difference
0.178 0.681 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.458
Model: OLS Adj. R-squared: 0.310
Method: Least Squares F-statistic: 3.094
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0716
Time: 06:23:20 Log-Likelihood: -70.712
No. Observations: 15 AIC: 149.4
Df Residuals: 11 BIC: 152.3
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 145.1751 239.526 0.606 0.557 -382.017 672.367
C(dose)[T.1] 15.5540 289.531 0.054 0.958 -621.700 652.808
expression -13.2375 40.732 -0.325 0.751 -102.889 76.414
expression:C(dose)[T.1] 6.1684 48.328 0.128 0.901 -100.201 112.538
Omnibus: 2.604 Durbin-Watson: 0.932
Prob(Omnibus): 0.272 Jarque-Bera (JB): 1.679
Skew: -0.808 Prob(JB): 0.432
Kurtosis: 2.731 Cond. No. 325.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.457
Model: OLS Adj. R-squared: 0.366
Method: Least Squares F-statistic: 5.046
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0257
Time: 06:23:20 Log-Likelihood: -70.723
No. Observations: 15 AIC: 147.4
Df Residuals: 12 BIC: 149.6
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 119.4399 123.885 0.964 0.354 -150.482 389.362
C(dose)[T.1] 52.4357 17.411 3.012 0.011 14.500 90.371
expression -8.8557 21.004 -0.422 0.681 -54.619 36.907
Omnibus: 2.666 Durbin-Watson: 0.906
Prob(Omnibus): 0.264 Jarque-Bera (JB): 1.658
Skew: -0.808 Prob(JB): 0.436
Kurtosis: 2.793 Cond. No. 99.9

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: 06:23:20 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: 0.046
Model: OLS Adj. R-squared: -0.027
Method: Least Squares F-statistic: 0.6307
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.441
Time: 06:23:20 Log-Likelihood: -74.945
No. Observations: 15 AIC: 153.9
Df Residuals: 13 BIC: 155.3
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -21.9712 145.949 -0.151 0.883 -337.275 293.333
expression 19.0561 23.996 0.794 0.441 -32.783 70.895
Omnibus: 0.558 Durbin-Watson: 1.425
Prob(Omnibus): 0.757 Jarque-Bera (JB): 0.562
Skew: -0.001 Prob(JB): 0.755
Kurtosis: 2.052 Cond. No. 91.9