LID SPN TRAP

1423786_at

8430410A17Rik RIKEN cDNA 8430410A17 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
3.089 0.094 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.722
Model: OLS Adj. R-squared: 0.678
Method: Least Squares F-statistic: 16.42
Date: Thu, 21 Nov 2024 Prob (F-statistic): 1.65e-05
Time: 06:20:47 Log-Likelihood: -98.398
No. Observations: 23 AIC: 204.8
Df Residuals: 19 BIC: 209.3
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 113.1539 128.081 0.883 0.388 -154.923 381.231
C(dose)[T.1] 314.6987 195.135 1.613 0.123 -93.724 723.121
expression -7.6814 16.675 -0.461 0.650 -42.583 27.220
expression:C(dose)[T.1] -33.2144 25.116 -1.322 0.202 -85.783 19.354
Omnibus: 1.790 Durbin-Watson: 1.596
Prob(Omnibus): 0.409 Jarque-Bera (JB): 1.482
Skew: 0.476 Prob(JB): 0.477
Kurtosis: 2.201 Cond. No. 486.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.696
Model: OLS Adj. R-squared: 0.666
Method: Least Squares F-statistic: 22.90
Date: Thu, 21 Nov 2024 Prob (F-statistic): 6.74e-06
Time: 06:20:47 Log-Likelihood: -99.411
No. Observations: 23 AIC: 204.8
Df Residuals: 20 BIC: 208.2
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 225.5040 97.628 2.310 0.032 21.856 429.152
C(dose)[T.1] 56.8747 8.407 6.765 0.000 39.339 74.411
expression -22.3222 12.701 -1.758 0.094 -48.816 4.172
Omnibus: 0.867 Durbin-Watson: 1.665
Prob(Omnibus): 0.648 Jarque-Bera (JB): 0.829
Skew: 0.395 Prob(JB): 0.661
Kurtosis: 2.509 Cond. No. 189.

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: 06:20:47 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: 0.006418
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.937
Time: 06:20:47 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 93.2664 169.276 0.551 0.587 -258.763 445.296
expression -1.7483 21.823 -0.080 0.937 -47.133 43.636
Omnibus: 3.435 Durbin-Watson: 2.486
Prob(Omnibus): 0.179 Jarque-Bera (JB): 1.589
Skew: 0.285 Prob(JB): 0.452
Kurtosis: 1.845 Cond. No. 185.

CP101

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

F-statistic p-value df difference
13.351 0.003 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.760
Model: OLS Adj. R-squared: 0.694
Method: Least Squares F-statistic: 11.61
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.000984
Time: 06:20:47 Log-Likelihood: -64.599
No. Observations: 15 AIC: 137.2
Df Residuals: 11 BIC: 140.0
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -337.0276 170.525 -1.976 0.074 -712.350 38.295
C(dose)[T.1] -245.1964 292.912 -0.837 0.420 -889.891 399.498
expression 50.9694 21.466 2.374 0.037 3.723 98.216
expression:C(dose)[T.1] 35.6679 36.492 0.977 0.349 -44.650 115.986
Omnibus: 2.151 Durbin-Watson: 1.316
Prob(Omnibus): 0.341 Jarque-Bera (JB): 0.536
Skew: 0.344 Prob(JB): 0.765
Kurtosis: 3.620 Cond. No. 549.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.739
Model: OLS Adj. R-squared: 0.696
Method: Least Squares F-statistic: 17.00
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.000316
Time: 06:20:47 Log-Likelihood: -65.224
No. Observations: 15 AIC: 136.4
Df Residuals: 12 BIC: 138.6
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -434.9672 137.722 -3.158 0.008 -735.038 -134.897
C(dose)[T.1] 40.8963 11.065 3.696 0.003 16.788 65.004
expression 63.3118 17.327 3.654 0.003 25.559 101.064
Omnibus: 0.589 Durbin-Watson: 1.454
Prob(Omnibus): 0.745 Jarque-Bera (JB): 0.015
Skew: 0.073 Prob(JB): 0.992
Kurtosis: 3.054 Cond. No. 208.

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: 06:20:47 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: 0.442
Model: OLS Adj. R-squared: 0.399
Method: Least Squares F-statistic: 10.30
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00685
Time: 06:20:47 Log-Likelihood: -70.924
No. Observations: 15 AIC: 145.8
Df Residuals: 13 BIC: 147.3
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -518.4082 190.878 -2.716 0.018 -930.776 -106.041
expression 76.4598 23.825 3.209 0.007 24.988 127.932
Omnibus: 1.242 Durbin-Watson: 1.988
Prob(Omnibus): 0.537 Jarque-Bera (JB): 0.936
Skew: 0.560 Prob(JB): 0.626
Kurtosis: 2.508 Cond. No. 205.