LID SPN TRAP

1428860_at

4930572J05Rik RIKEN cDNA 4930572J05 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
2.098 0.163 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.692
Model: OLS Adj. R-squared: 0.643
Method: Least Squares F-statistic: 14.21
Date: Thu, 21 Nov 2024 Prob (F-statistic): 4.28e-05
Time: 05:03:57 Log-Likelihood: -99.573
No. Observations: 23 AIC: 207.1
Df Residuals: 19 BIC: 211.7
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 205.0629 106.833 1.919 0.070 -18.542 428.668
C(dose)[T.1] -43.0300 127.169 -0.338 0.739 -309.198 223.138
expression -25.8064 18.249 -1.414 0.173 -64.001 12.388
expression:C(dose)[T.1] 16.4721 21.716 0.759 0.457 -28.979 61.924
Omnibus: 0.016 Durbin-Watson: 1.930
Prob(Omnibus): 0.992 Jarque-Bera (JB): 0.203
Skew: -0.038 Prob(JB): 0.904
Kurtosis: 2.547 Cond. No. 259.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.682
Model: OLS Adj. R-squared: 0.651
Method: Least Squares F-statistic: 21.48
Date: Thu, 21 Nov 2024 Prob (F-statistic): 1.05e-05
Time: 05:03:57 Log-Likelihood: -99.916
No. Observations: 23 AIC: 205.8
Df Residuals: 20 BIC: 209.2
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 137.0663 57.497 2.384 0.027 17.129 257.003
C(dose)[T.1] 53.2196 8.344 6.379 0.000 35.815 70.624
expression -14.1743 9.786 -1.448 0.163 -34.588 6.239
Omnibus: 0.132 Durbin-Watson: 1.872
Prob(Omnibus): 0.936 Jarque-Bera (JB): 0.340
Skew: -0.100 Prob(JB): 0.844
Kurtosis: 2.439 Cond. No. 83.4

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: 05:03:57 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: 0.036
Model: OLS Adj. R-squared: -0.010
Method: Least Squares F-statistic: 0.7895
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.384
Time: 05:03:57 Log-Likelihood: -112.68
No. Observations: 23 AIC: 229.4
Df Residuals: 21 BIC: 231.6
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 166.0641 97.436 1.704 0.103 -36.564 368.692
expression -14.7812 16.635 -0.889 0.384 -49.376 19.814
Omnibus: 4.190 Durbin-Watson: 2.442
Prob(Omnibus): 0.123 Jarque-Bera (JB): 1.784
Skew: 0.319 Prob(JB): 0.410
Kurtosis: 1.793 Cond. No. 82.9

CP101

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

F-statistic p-value df difference
4.633 0.052 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.737
Model: OLS Adj. R-squared: 0.666
Method: Least Squares F-statistic: 10.29
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00160
Time: 05:03:57 Log-Likelihood: -65.277
No. Observations: 15 AIC: 138.6
Df Residuals: 11 BIC: 141.4
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 355.0326 275.817 1.287 0.224 -252.036 962.101
C(dose)[T.1] -653.8613 303.065 -2.157 0.054 -1320.903 13.180
expression -39.1579 37.536 -1.043 0.319 -121.774 43.458
expression:C(dose)[T.1] 98.9553 41.647 2.376 0.037 7.291 190.620
Omnibus: 1.333 Durbin-Watson: 0.920
Prob(Omnibus): 0.513 Jarque-Bera (JB): 0.733
Skew: -0.532 Prob(JB): 0.693
Kurtosis: 2.801 Cond. No. 591.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.602
Model: OLS Adj. R-squared: 0.536
Method: Least Squares F-statistic: 9.088
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00396
Time: 05:03:57 Log-Likelihood: -68.384
No. Observations: 15 AIC: 142.8
Df Residuals: 12 BIC: 144.9
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -235.3618 141.006 -1.669 0.121 -542.586 71.863
C(dose)[T.1] 65.5651 15.380 4.263 0.001 32.054 99.076
expression 41.2255 19.152 2.153 0.052 -0.503 82.954
Omnibus: 3.974 Durbin-Watson: 0.815
Prob(Omnibus): 0.137 Jarque-Bera (JB): 2.279
Skew: -0.953 Prob(JB): 0.320
Kurtosis: 3.102 Cond. No. 155.

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: 05:03:57 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: 0.000
Model: OLS Adj. R-squared: -0.077
Method: Least Squares F-statistic: 0.001147
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.974
Time: 05:03:57 Log-Likelihood: -75.299
No. Observations: 15 AIC: 154.6
Df Residuals: 13 BIC: 156.0
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 87.5411 181.191 0.483 0.637 -303.897 478.979
expression 0.8588 25.362 0.034 0.974 -53.932 55.650
Omnibus: 0.539 Durbin-Watson: 1.628
Prob(Omnibus): 0.764 Jarque-Bera (JB): 0.556
Skew: 0.038 Prob(JB): 0.757
Kurtosis: 2.060 Cond. No. 130.