LID SPN TRAP

1449072_a_at

N6amt2 N-6 adenine-specific DNA methyltransferase 2 (putative)

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
0.421 0.524 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.697
Model: OLS Adj. R-squared: 0.649
Method: Least Squares F-statistic: 14.54
Date: Tue, 28 Jan 2025 Prob (F-statistic): 3.70e-05
Time: 18:19:19 Log-Likelihood: -99.390
No. Observations: 23 AIC: 206.8
Df Residuals: 19 BIC: 211.3
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -481.1027 344.749 -1.396 0.179 -1202.670 240.464
C(dose)[T.1] 883.7687 522.916 1.690 0.107 -210.706 1978.244
expression 52.0933 33.544 1.553 0.137 -18.115 122.302
expression:C(dose)[T.1] -80.8116 50.879 -1.588 0.129 -187.304 25.680
Omnibus: 0.315 Durbin-Watson: 1.861
Prob(Omnibus): 0.854 Jarque-Bera (JB): 0.480
Skew: -0.038 Prob(JB): 0.787
Kurtosis: 2.296 Cond. No. 1.64e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.656
Model: OLS Adj. R-squared: 0.622
Method: Least Squares F-statistic: 19.09
Date: Tue, 28 Jan 2025 Prob (F-statistic): 2.30e-05
Time: 18:19:19 Log-Likelihood: -100.82
No. Observations: 23 AIC: 207.6
Df Residuals: 20 BIC: 211.1
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -120.1523 268.929 -0.447 0.660 -681.128 440.824
C(dose)[T.1] 53.3304 8.679 6.145 0.000 35.226 71.435
expression 16.9678 26.164 0.649 0.524 -37.610 71.545
Omnibus: 0.247 Durbin-Watson: 1.857
Prob(Omnibus): 0.884 Jarque-Bera (JB): 0.429
Skew: -0.157 Prob(JB): 0.807
Kurtosis: 2.409 Cond. No. 644.

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: Tue, 28 Jan 2025 Prob (F-statistic): 3.51e-06
Time: 18:19:19 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: 0.007
Model: OLS Adj. R-squared: -0.040
Method: Least Squares F-statistic: 0.1564
Date: Tue, 28 Jan 2025 Prob (F-statistic): 0.696
Time: 18:19:19 Log-Likelihood: -113.02
No. Observations: 23 AIC: 230.0
Df Residuals: 21 BIC: 232.3
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -96.6202 445.952 -0.217 0.831 -1024.028 830.787
expression 17.1598 43.391 0.395 0.696 -73.077 107.396
Omnibus: 3.313 Durbin-Watson: 2.437
Prob(Omnibus): 0.191 Jarque-Bera (JB): 1.646
Skew: 0.333 Prob(JB): 0.439
Kurtosis: 1.871 Cond. No. 643.

CP101

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

F-statistic p-value df difference
4.032 0.068 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.616
Model: OLS Adj. R-squared: 0.511
Method: Least Squares F-statistic: 5.870
Date: Tue, 28 Jan 2025 Prob (F-statistic): 0.0121
Time: 18:19:19 Log-Likelihood: -68.131
No. Observations: 15 AIC: 144.3
Df Residuals: 11 BIC: 147.1
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -287.3197 285.744 -1.006 0.336 -916.238 341.598
C(dose)[T.1] -455.4304 557.276 -0.817 0.431 -1681.987 771.126
expression 33.6632 27.098 1.242 0.240 -25.980 93.307
expression:C(dose)[T.1] 47.0605 52.472 0.897 0.389 -68.429 162.550
Omnibus: 0.382 Durbin-Watson: 0.998
Prob(Omnibus): 0.826 Jarque-Bera (JB): 0.506
Skew: -0.188 Prob(JB): 0.777
Kurtosis: 2.183 Cond. No. 1.05e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.587
Model: OLS Adj. R-squared: 0.519
Method: Least Squares F-statistic: 8.542
Date: Tue, 28 Jan 2025 Prob (F-statistic): 0.00493
Time: 18:19:19 Log-Likelihood: -68.660
No. Observations: 15 AIC: 143.3
Df Residuals: 12 BIC: 145.4
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -419.5887 242.741 -1.729 0.110 -948.476 109.299
C(dose)[T.1] 44.2177 13.841 3.195 0.008 14.060 74.375
expression 46.2147 23.015 2.008 0.068 -3.931 96.360
Omnibus: 1.057 Durbin-Watson: 1.119
Prob(Omnibus): 0.589 Jarque-Bera (JB): 0.874
Skew: -0.514 Prob(JB): 0.646
Kurtosis: 2.415 Cond. No. 383.

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: Tue, 28 Jan 2025 Prob (F-statistic): 0.00629
Time: 18:19:19 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: 0.237
Model: OLS Adj. R-squared: 0.178
Method: Least Squares F-statistic: 4.027
Date: Tue, 28 Jan 2025 Prob (F-statistic): 0.0660
Time: 18:19:19 Log-Likelihood: -73.276
No. Observations: 15 AIC: 150.6
Df Residuals: 13 BIC: 152.0
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -535.5598 313.685 -1.707 0.112 -1213.234 142.115
expression 59.3856 29.593 2.007 0.066 -4.547 123.318
Omnibus: 0.119 Durbin-Watson: 1.721
Prob(Omnibus): 0.942 Jarque-Bera (JB): 0.325
Skew: 0.122 Prob(JB): 0.850
Kurtosis: 2.321 Cond. No. 378.