LID SPN TRAP

1452082_at

6430548M08Rik RIKEN cDNA 6430548M08 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
1.932 0.180 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.683
Model: OLS Adj. R-squared: 0.633
Method: Least Squares F-statistic: 13.63
Date: Thu, 21 Nov 2024 Prob (F-statistic): 5.60e-05
Time: 05:19:26 Log-Likelihood: -99.903
No. Observations: 23 AIC: 207.8
Df Residuals: 19 BIC: 212.3
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -65.0693 127.740 -0.509 0.616 -332.433 202.294
C(dose)[T.1] -49.5239 244.064 -0.203 0.841 -560.355 461.307
expression 15.8799 16.988 0.935 0.362 -19.677 51.437
expression:C(dose)[T.1] 12.9335 31.869 0.406 0.689 -53.768 79.635
Omnibus: 0.294 Durbin-Watson: 2.111
Prob(Omnibus): 0.863 Jarque-Bera (JB): 0.145
Skew: 0.176 Prob(JB): 0.930
Kurtosis: 2.831 Cond. No. 526.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.680
Model: OLS Adj. R-squared: 0.648
Method: Least Squares F-statistic: 21.25
Date: Thu, 21 Nov 2024 Prob (F-statistic): 1.13e-05
Time: 05:19:26 Log-Likelihood: -100.00
No. Observations: 23 AIC: 206.0
Df Residuals: 20 BIC: 209.4
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -92.6751 105.841 -0.876 0.392 -313.456 128.106
C(dose)[T.1] 49.4588 8.827 5.603 0.000 31.045 67.872
expression 19.5552 14.070 1.390 0.180 -9.794 48.905
Omnibus: 0.146 Durbin-Watson: 2.129
Prob(Omnibus): 0.930 Jarque-Bera (JB): 0.151
Skew: 0.141 Prob(JB): 0.927
Kurtosis: 2.719 Cond. No. 196.

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: 05:19:26 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: 0.178
Model: OLS Adj. R-squared: 0.138
Method: Least Squares F-statistic: 4.536
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0452
Time: 05:19:26 Log-Likelihood: -110.86
No. Observations: 23 AIC: 225.7
Df Residuals: 21 BIC: 228.0
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -258.5642 158.964 -1.627 0.119 -589.148 72.020
expression 44.4751 20.882 2.130 0.045 1.049 87.901
Omnibus: 1.167 Durbin-Watson: 2.449
Prob(Omnibus): 0.558 Jarque-Bera (JB): 0.959
Skew: 0.258 Prob(JB): 0.619
Kurtosis: 2.143 Cond. No. 188.

CP101

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

F-statistic p-value df difference
2.066 0.176 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.581
Model: OLS Adj. R-squared: 0.467
Method: Least Squares F-statistic: 5.087
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0189
Time: 05:19:26 Log-Likelihood: -68.774
No. Observations: 15 AIC: 145.5
Df Residuals: 11 BIC: 148.4
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -250.4922 171.406 -1.461 0.172 -627.754 126.769
C(dose)[T.1] 404.4870 305.439 1.324 0.212 -267.780 1076.754
expression 43.3147 23.309 1.858 0.090 -7.989 94.618
expression:C(dose)[T.1] -48.4298 41.701 -1.161 0.270 -140.213 43.354
Omnibus: 4.867 Durbin-Watson: 1.224
Prob(Omnibus): 0.088 Jarque-Bera (JB): 2.391
Skew: -0.923 Prob(JB): 0.303
Kurtosis: 3.646 Cond. No. 392.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.530
Model: OLS Adj. R-squared: 0.451
Method: Least Squares F-statistic: 6.759
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0108
Time: 05:19:26 Log-Likelihood: -69.641
No. Observations: 15 AIC: 145.3
Df Residuals: 12 BIC: 147.4
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -139.4305 144.301 -0.966 0.353 -453.835 174.974
C(dose)[T.1] 50.1545 14.553 3.446 0.005 18.446 81.863
expression 28.1832 19.607 1.437 0.176 -14.536 70.903
Omnibus: 3.608 Durbin-Watson: 0.858
Prob(Omnibus): 0.165 Jarque-Bera (JB): 2.053
Skew: -0.906 Prob(JB): 0.358
Kurtosis: 3.058 Cond. No. 149.

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: 05:19:26 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: 0.064
Model: OLS Adj. R-squared: -0.008
Method: Least Squares F-statistic: 0.8933
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.362
Time: 05:19:26 Log-Likelihood: -74.802
No. Observations: 15 AIC: 153.6
Df Residuals: 13 BIC: 155.0
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -90.0236 194.596 -0.463 0.651 -510.423 330.376
expression 25.0886 26.544 0.945 0.362 -32.257 82.434
Omnibus: 5.035 Durbin-Watson: 1.636
Prob(Omnibus): 0.081 Jarque-Bera (JB): 1.783
Skew: 0.439 Prob(JB): 0.410
Kurtosis: 1.558 Cond. No. 148.