LID SPN TRAP

1460651_at

Lat linker for activation of T cells

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
1.068 0.314 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.673
Model: OLS Adj. R-squared: 0.621
Method: Least Squares F-statistic: 13.02
Date: Thu, 21 Nov 2024 Prob (F-statistic): 7.45e-05
Time: 05:07:13 Log-Likelihood: -100.26
No. Observations: 23 AIC: 208.5
Df Residuals: 19 BIC: 213.1
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 73.0975 105.712 0.691 0.498 -148.161 294.356
C(dose)[T.1] -20.4796 115.994 -0.177 0.862 -263.258 222.299
expression -5.3857 30.092 -0.179 0.860 -68.369 57.597
expression:C(dose)[T.1] 18.9820 32.292 0.588 0.564 -48.606 86.570
Omnibus: 0.372 Durbin-Watson: 1.978
Prob(Omnibus): 0.830 Jarque-Bera (JB): 0.519
Skew: 0.108 Prob(JB): 0.772
Kurtosis: 2.297 Cond. No. 168.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.667
Model: OLS Adj. R-squared: 0.634
Method: Least Squares F-statistic: 20.02
Date: Thu, 21 Nov 2024 Prob (F-statistic): 1.68e-05
Time: 05:07:13 Log-Likelihood: -100.46
No. Observations: 23 AIC: 206.9
Df Residuals: 20 BIC: 210.3
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 15.2850 38.120 0.401 0.693 -64.232 94.802
C(dose)[T.1] 47.4267 10.282 4.613 0.000 25.980 68.874
expression 11.0978 10.737 1.034 0.314 -11.300 33.496
Omnibus: 0.216 Durbin-Watson: 1.929
Prob(Omnibus): 0.898 Jarque-Bera (JB): 0.393
Skew: 0.165 Prob(JB): 0.822
Kurtosis: 2.451 Cond. No. 36.9

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: 05:07:13 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: 0.312
Model: OLS Adj. R-squared: 0.280
Method: Least Squares F-statistic: 9.542
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00556
Time: 05:07:13 Log-Likelihood: -108.80
No. Observations: 23 AIC: 221.6
Df Residuals: 21 BIC: 223.9
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -65.6656 47.444 -1.384 0.181 -164.331 32.999
expression 38.6450 12.511 3.089 0.006 12.628 64.662
Omnibus: 1.052 Durbin-Watson: 2.517
Prob(Omnibus): 0.591 Jarque-Bera (JB): 0.931
Skew: 0.280 Prob(JB): 0.628
Kurtosis: 2.189 Cond. No. 32.1

CP101

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

F-statistic p-value df difference
2.704 0.126 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.574
Model: OLS Adj. R-squared: 0.458
Method: Least Squares F-statistic: 4.941
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0206
Time: 05:07:13 Log-Likelihood: -68.900
No. Observations: 15 AIC: 145.8
Df Residuals: 11 BIC: 148.6
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 220.6352 161.422 1.367 0.199 -134.652 575.923
C(dose)[T.1] 315.2334 318.771 0.989 0.344 -386.376 1016.843
expression -45.8442 48.199 -0.951 0.362 -151.930 60.241
expression:C(dose)[T.1] -71.0799 90.513 -0.785 0.449 -270.297 128.137
Omnibus: 0.466 Durbin-Watson: 1.085
Prob(Omnibus): 0.792 Jarque-Bera (JB): 0.506
Skew: -0.334 Prob(JB): 0.777
Kurtosis: 2.397 Cond. No. 204.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.550
Model: OLS Adj. R-squared: 0.475
Method: Least Squares F-statistic: 7.337
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00829
Time: 05:07:13 Log-Likelihood: -69.309
No. Observations: 15 AIC: 144.6
Df Residuals: 12 BIC: 146.7
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 287.9948 134.545 2.141 0.054 -5.154 581.143
C(dose)[T.1] 65.2811 17.259 3.782 0.003 27.677 102.886
expression -66.0003 40.140 -1.644 0.126 -153.458 21.457
Omnibus: 0.893 Durbin-Watson: 1.066
Prob(Omnibus): 0.640 Jarque-Bera (JB): 0.777
Skew: -0.469 Prob(JB): 0.678
Kurtosis: 2.396 Cond. No. 72.6

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: 05:07:13 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: 0.014
Model: OLS Adj. R-squared: -0.062
Method: Least Squares F-statistic: 0.1817
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.677
Time: 05:07:13 Log-Likelihood: -75.196
No. Observations: 15 AIC: 154.4
Df Residuals: 13 BIC: 155.8
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 24.0446 163.637 0.147 0.885 -329.473 377.562
expression 20.0532 47.043 0.426 0.677 -81.576 121.683
Omnibus: 0.240 Durbin-Watson: 1.529
Prob(Omnibus): 0.887 Jarque-Bera (JB): 0.420
Skew: -0.072 Prob(JB): 0.811
Kurtosis: 2.193 Cond. No. 61.1