LID SPN TRAP

1458202_at

Fam65b family with sequence similarity 65, member B

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
2.566 0.125 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: 0.644
Method: Least Squares F-statistic: 14.26
Date: Thu, 21 Nov 2024 Prob (F-statistic): 4.19e-05
Time: 05:02:53 Log-Likelihood: -99.546
No. Observations: 23 AIC: 207.1
Df Residuals: 19 BIC: 211.6
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -127.3022 177.246 -0.718 0.481 -498.283 243.679
C(dose)[T.1] -102.0544 318.043 -0.321 0.752 -767.726 563.617
expression 22.5774 22.035 1.025 0.318 -23.543 68.697
expression:C(dose)[T.1] 17.8204 38.570 0.462 0.649 -62.909 98.549
Omnibus: 0.610 Durbin-Watson: 1.558
Prob(Omnibus): 0.737 Jarque-Bera (JB): 0.651
Skew: 0.138 Prob(JB): 0.722
Kurtosis: 2.224 Cond. No. 759.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.689
Model: OLS Adj. R-squared: 0.658
Method: Least Squares F-statistic: 22.15
Date: Thu, 21 Nov 2024 Prob (F-statistic): 8.48e-06
Time: 05:02:53 Log-Likelihood: -99.675
No. Observations: 23 AIC: 205.3
Df Residuals: 20 BIC: 208.8
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -174.0611 142.622 -1.220 0.236 -471.566 123.444
C(dose)[T.1] 44.8151 9.822 4.563 0.000 24.327 65.303
expression 28.3936 17.726 1.602 0.125 -8.582 65.369
Omnibus: 0.804 Durbin-Watson: 1.566
Prob(Omnibus): 0.669 Jarque-Bera (JB): 0.716
Skew: 0.083 Prob(JB): 0.699
Kurtosis: 2.151 Cond. No. 288.

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: 05:02:53 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: 0.365
Model: OLS Adj. R-squared: 0.335
Method: Least Squares F-statistic: 12.08
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00226
Time: 05:02:53 Log-Likelihood: -107.88
No. Observations: 23 AIC: 219.8
Df Residuals: 21 BIC: 222.0
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -511.1271 170.089 -3.005 0.007 -864.847 -157.407
expression 72.2037 20.774 3.476 0.002 29.002 115.405
Omnibus: 0.130 Durbin-Watson: 2.363
Prob(Omnibus): 0.937 Jarque-Bera (JB): 0.316
Skew: 0.130 Prob(JB): 0.854
Kurtosis: 2.488 Cond. No. 246.

CP101

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

F-statistic p-value df difference
5.509 0.037 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.623
Model: OLS Adj. R-squared: 0.520
Method: Least Squares F-statistic: 6.051
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0109
Time: 05:02:53 Log-Likelihood: -67.990
No. Observations: 15 AIC: 144.0
Df Residuals: 11 BIC: 146.8
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 355.6054 175.359 2.028 0.067 -30.357 741.568
C(dose)[T.1] 17.7185 242.374 0.073 0.943 -515.742 551.179
expression -40.6530 24.698 -1.646 0.128 -95.013 13.707
expression:C(dose)[T.1] 4.0970 34.292 0.119 0.907 -71.380 79.574
Omnibus: 0.602 Durbin-Watson: 1.350
Prob(Omnibus): 0.740 Jarque-Bera (JB): 0.579
Skew: -0.017 Prob(JB): 0.749
Kurtosis: 2.038 Cond. No. 345.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.622
Model: OLS Adj. R-squared: 0.559
Method: Least Squares F-statistic: 9.882
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00291
Time: 05:02:53 Log-Likelihood: -68.000
No. Observations: 15 AIC: 142.0
Df Residuals: 12 BIC: 144.1
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 340.5404 116.752 2.917 0.013 86.160 594.921
C(dose)[T.1] 46.6299 13.076 3.566 0.004 18.139 75.121
expression -38.5278 16.415 -2.347 0.037 -74.294 -2.762
Omnibus: 0.726 Durbin-Watson: 1.321
Prob(Omnibus): 0.696 Jarque-Bera (JB): 0.622
Skew: 0.023 Prob(JB): 0.733
Kurtosis: 2.003 Cond. No. 130.

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: 05:02:53 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: 0.222
Model: OLS Adj. R-squared: 0.162
Method: Least Squares F-statistic: 3.706
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0764
Time: 05:02:53 Log-Likelihood: -73.419
No. Observations: 15 AIC: 150.8
Df Residuals: 13 BIC: 152.3
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 399.9363 159.338 2.510 0.026 55.707 744.166
expression -43.4230 22.555 -1.925 0.076 -92.151 5.305
Omnibus: 1.841 Durbin-Watson: 1.648
Prob(Omnibus): 0.398 Jarque-Bera (JB): 1.452
Skew: 0.652 Prob(JB): 0.484
Kurtosis: 2.213 Cond. No. 128.