LID SPN TRAP

1443523_at

Fam135b family with sequence similarity 135, 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
2.784 0.111 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.694
Model: OLS Adj. R-squared: 0.646
Method: Least Squares F-statistic: 14.37
Date: Thu, 03 Apr 2025 Prob (F-statistic): 3.98e-05
Time: 22:44:36 Log-Likelihood: -99.482
No. Observations: 23 AIC: 207.0
Df Residuals: 19 BIC: 211.5
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 184.1365 91.421 2.014 0.058 -7.210 375.483
C(dose)[T.1] 5.1382 130.591 0.039 0.969 -268.191 278.468
expression -18.3656 12.896 -1.424 0.171 -45.358 8.627
expression:C(dose)[T.1] 6.7997 18.432 0.369 0.716 -31.779 45.378
Omnibus: 0.911 Durbin-Watson: 2.051
Prob(Omnibus): 0.634 Jarque-Bera (JB): 0.861
Skew: 0.272 Prob(JB): 0.650
Kurtosis: 2.223 Cond. No. 290.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.692
Model: OLS Adj. R-squared: 0.661
Method: Least Squares F-statistic: 22.46
Date: Thu, 03 Apr 2025 Prob (F-statistic): 7.70e-06
Time: 22:44:37 Log-Likelihood: -99.564
No. Observations: 23 AIC: 205.1
Df Residuals: 20 BIC: 208.5
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 160.5868 64.014 2.509 0.021 27.057 294.117
C(dose)[T.1] 53.2145 8.217 6.476 0.000 36.074 70.355
expression -15.0368 9.013 -1.668 0.111 -33.837 3.763
Omnibus: 1.199 Durbin-Watson: 2.059
Prob(Omnibus): 0.549 Jarque-Bera (JB): 1.074
Skew: 0.364 Prob(JB): 0.585
Kurtosis: 2.232 Cond. No. 113.

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, 03 Apr 2025 Prob (F-statistic): 3.51e-06
Time: 22:44:37 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: 0.046
Model: OLS Adj. R-squared: 0.000
Method: Least Squares F-statistic: 1.010
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.326
Time: 22:44:37 Log-Likelihood: -112.56
No. Observations: 23 AIC: 229.1
Df Residuals: 21 BIC: 231.4
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 189.7288 109.666 1.730 0.098 -38.335 417.793
expression -15.5589 15.478 -1.005 0.326 -47.747 16.629
Omnibus: 1.915 Durbin-Watson: 2.650
Prob(Omnibus): 0.384 Jarque-Bera (JB): 1.430
Skew: 0.414 Prob(JB): 0.489
Kurtosis: 2.102 Cond. No. 112.

CP101

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

F-statistic p-value df difference
1.635 0.225 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.557
Model: OLS Adj. R-squared: 0.437
Method: Least Squares F-statistic: 4.617
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.0252
Time: 22:44:37 Log-Likelihood: -69.187
No. Observations: 15 AIC: 146.4
Df Residuals: 11 BIC: 149.2
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -4.2457 315.694 -0.013 0.990 -699.084 690.593
C(dose)[T.1] 403.8740 360.576 1.120 0.287 -389.748 1197.496
expression 8.7781 38.641 0.227 0.824 -76.271 93.827
expression:C(dose)[T.1] -46.2280 44.976 -1.028 0.326 -145.220 52.764
Omnibus: 1.576 Durbin-Watson: 0.913
Prob(Omnibus): 0.455 Jarque-Bera (JB): 1.269
Skew: -0.585 Prob(JB): 0.530
Kurtosis: 2.187 Cond. No. 576.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.515
Model: OLS Adj. R-squared: 0.434
Method: Least Squares F-statistic: 6.368
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.0130
Time: 22:44:37 Log-Likelihood: -69.875
No. Observations: 15 AIC: 145.7
Df Residuals: 12 BIC: 147.9
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 274.3678 162.195 1.692 0.117 -79.024 627.760
C(dose)[T.1] 33.7799 19.063 1.772 0.102 -7.754 75.314
expression -25.3443 19.820 -1.279 0.225 -68.529 17.841
Omnibus: 1.956 Durbin-Watson: 0.770
Prob(Omnibus): 0.376 Jarque-Bera (JB): 1.088
Skew: -0.307 Prob(JB): 0.580
Kurtosis: 1.832 Cond. No. 177.

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, 03 Apr 2025 Prob (F-statistic): 0.00629
Time: 22:44:37 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: 0.388
Model: OLS Adj. R-squared: 0.341
Method: Least Squares F-statistic: 8.239
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.0131
Time: 22:44:37 Log-Likelihood: -71.618
No. Observations: 15 AIC: 147.2
Df Residuals: 13 BIC: 148.7
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 466.5547 130.150 3.585 0.003 185.383 747.727
expression -47.5579 16.568 -2.870 0.013 -83.352 -11.764
Omnibus: 2.210 Durbin-Watson: 1.100
Prob(Omnibus): 0.331 Jarque-Bera (JB): 0.987
Skew: 0.030 Prob(JB): 0.611
Kurtosis: 1.745 Cond. No. 131.