LID SPN TRAP

1418003_at

1190002H23Rik RIKEN cDNA 1190002H23 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
0.002 0.967 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.793
Model: OLS Adj. R-squared: 0.761
Method: Least Squares F-statistic: 24.33
Date: Thu, 21 Nov 2024 Prob (F-statistic): 1.01e-06
Time: 04:03:38 Log-Likelihood: -94.965
No. Observations: 23 AIC: 197.9
Df Residuals: 19 BIC: 202.5
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -212.6760 129.759 -1.639 0.118 -484.265 58.913
C(dose)[T.1] 914.0787 236.286 3.869 0.001 419.526 1408.632
expression 30.5514 14.844 2.058 0.054 -0.518 61.620
expression:C(dose)[T.1] -97.9063 26.863 -3.645 0.002 -154.132 -41.681
Omnibus: 2.209 Durbin-Watson: 1.796
Prob(Omnibus): 0.331 Jarque-Bera (JB): 1.899
Skew: -0.632 Prob(JB): 0.387
Kurtosis: 2.380 Cond. No. 730.

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: 04:03:38 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 48.4723 137.444 0.353 0.728 -238.231 335.176
C(dose)[T.1] 53.2838 8.862 6.013 0.000 34.798 71.770
expression 0.6566 15.719 0.042 0.967 -32.132 33.445
Omnibus: 0.313 Durbin-Watson: 1.890
Prob(Omnibus): 0.855 Jarque-Bera (JB): 0.479
Skew: 0.049 Prob(JB): 0.787
Kurtosis: 2.300 Cond. No. 279.

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: 04:03:38 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: 0.015
Model: OLS Adj. R-squared: -0.032
Method: Least Squares F-statistic: 0.3151
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.581
Time: 04:03:38 Log-Likelihood: -112.93
No. Observations: 23 AIC: 229.9
Df Residuals: 21 BIC: 232.1
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -45.5593 223.289 -0.204 0.840 -509.915 418.797
expression 14.2775 25.435 0.561 0.581 -38.617 67.172
Omnibus: 2.486 Durbin-Watson: 2.483
Prob(Omnibus): 0.289 Jarque-Bera (JB): 1.653
Skew: 0.437 Prob(JB): 0.438
Kurtosis: 2.020 Cond. No. 277.

CP101

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

F-statistic p-value df difference
1.277 0.281 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.533
Model: OLS Adj. R-squared: 0.406
Method: Least Squares F-statistic: 4.193
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0331
Time: 04:03:38 Log-Likelihood: -69.581
No. Observations: 15 AIC: 147.2
Df Residuals: 11 BIC: 150.0
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 85.0557 228.595 0.372 0.717 -418.079 588.190
C(dose)[T.1] -197.5736 280.582 -0.704 0.496 -815.129 419.982
expression -2.4809 32.136 -0.077 0.940 -73.212 68.250
expression:C(dose)[T.1] 33.7500 39.034 0.865 0.406 -52.164 119.664
Omnibus: 1.534 Durbin-Watson: 0.725
Prob(Omnibus): 0.464 Jarque-Bera (JB): 1.209
Skew: -0.530 Prob(JB): 0.546
Kurtosis: 2.100 Cond. No. 395.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.502
Model: OLS Adj. R-squared: 0.419
Method: Least Squares F-statistic: 6.043
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0153
Time: 04:03:38 Log-Likelihood: -70.075
No. Observations: 15 AIC: 146.1
Df Residuals: 12 BIC: 148.3
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -77.4760 128.700 -0.602 0.558 -357.890 202.938
C(dose)[T.1] 44.6466 15.496 2.881 0.014 10.884 78.409
expression 20.3947 18.049 1.130 0.281 -18.930 59.719
Omnibus: 3.020 Durbin-Watson: 0.955
Prob(Omnibus): 0.221 Jarque-Bera (JB): 1.579
Skew: -0.503 Prob(JB): 0.454
Kurtosis: 1.769 Cond. No. 128.

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: 04:03:38 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: 0.157
Model: OLS Adj. R-squared: 0.092
Method: Least Squares F-statistic: 2.424
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.144
Time: 04:03:38 Log-Likelihood: -74.018
No. Observations: 15 AIC: 152.0
Df Residuals: 13 BIC: 153.5
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -151.2756 157.613 -0.960 0.355 -491.778 189.227
expression 33.9068 21.780 1.557 0.144 -13.146 80.959
Omnibus: 0.124 Durbin-Watson: 1.553
Prob(Omnibus): 0.940 Jarque-Bera (JB): 0.345
Skew: -0.038 Prob(JB): 0.842
Kurtosis: 2.261 Cond. No. 125.