LID SPN TRAP

1425990_a_at

Nfatc2 nuclear factor of activated T-cells, cytoplasmic, calcineurin-dependent 2

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
0.006 0.938 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.662
Model: OLS Adj. R-squared: 0.609
Method: Least Squares F-statistic: 12.40
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.000101
Time: 04:56:49 Log-Likelihood: -100.63
No. Observations: 23 AIC: 209.3
Df Residuals: 19 BIC: 213.8
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 24.2911 47.572 0.511 0.616 -75.278 123.860
C(dose)[T.1] 102.9008 59.266 1.736 0.099 -21.144 226.946
expression 6.3250 9.974 0.634 0.534 -14.551 27.201
expression:C(dose)[T.1] -10.4895 12.401 -0.846 0.408 -36.446 15.467
Omnibus: 0.199 Durbin-Watson: 1.925
Prob(Omnibus): 0.905 Jarque-Bera (JB): 0.405
Skew: 0.038 Prob(JB): 0.817
Kurtosis: 2.355 Cond. No. 92.8

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.649
Model: OLS Adj. R-squared: 0.614
Method: Least Squares F-statistic: 18.50
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.83e-05
Time: 04:56:49 Log-Likelihood: -101.06
No. Observations: 23 AIC: 208.1
Df Residuals: 20 BIC: 211.5
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 56.3862 28.488 1.979 0.062 -3.039 115.811
C(dose)[T.1] 53.3314 8.769 6.082 0.000 35.040 71.623
expression -0.4604 5.885 -0.078 0.938 -12.736 11.815
Omnibus: 0.283 Durbin-Watson: 1.881
Prob(Omnibus): 0.868 Jarque-Bera (JB): 0.461
Skew: 0.061 Prob(JB): 0.794
Kurtosis: 2.317 Cond. No. 32.6

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: 04:56:49 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: 0.000
Model: OLS Adj. R-squared: -0.047
Method: Least Squares F-statistic: 0.006120
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.938
Time: 04:56:49 Log-Likelihood: -113.10
No. Observations: 23 AIC: 230.2
Df Residuals: 21 BIC: 232.5
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 83.2999 46.360 1.797 0.087 -13.112 179.712
expression -0.7584 9.694 -0.078 0.938 -20.918 19.401
Omnibus: 3.278 Durbin-Watson: 2.495
Prob(Omnibus): 0.194 Jarque-Bera (JB): 1.551
Skew: 0.281 Prob(JB): 0.461
Kurtosis: 1.858 Cond. No. 32.0

CP101

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

F-statistic p-value df difference
0.408 0.535 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.657
Model: OLS Adj. R-squared: 0.564
Method: Least Squares F-statistic: 7.026
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00660
Time: 04:56:49 Log-Likelihood: -67.273
No. Observations: 15 AIC: 142.5
Df Residuals: 11 BIC: 145.4
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 256.1774 166.237 1.541 0.152 -109.708 622.063
C(dose)[T.1] -493.2189 225.669 -2.186 0.051 -989.913 3.476
expression -25.2715 22.221 -1.137 0.280 -74.180 23.637
expression:C(dose)[T.1] 80.0745 32.422 2.470 0.031 8.715 151.434
Omnibus: 0.466 Durbin-Watson: 1.674
Prob(Omnibus): 0.792 Jarque-Bera (JB): 0.528
Skew: 0.047 Prob(JB): 0.768
Kurtosis: 2.086 Cond. No. 325.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.467
Model: OLS Adj. R-squared: 0.378
Method: Least Squares F-statistic: 5.255
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0230
Time: 04:56:49 Log-Likelihood: -70.582
No. Observations: 15 AIC: 147.2
Df Residuals: 12 BIC: 149.3
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -24.7613 144.710 -0.171 0.867 -340.057 290.534
C(dose)[T.1] 61.7302 24.986 2.471 0.029 7.291 116.170
expression 12.3432 19.316 0.639 0.535 -29.743 54.429
Omnibus: 1.480 Durbin-Watson: 0.838
Prob(Omnibus): 0.477 Jarque-Bera (JB): 1.198
Skew: -0.600 Prob(JB): 0.549
Kurtosis: 2.312 Cond. No. 135.

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: 04:56:49 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: 0.196
Model: OLS Adj. R-squared: 0.134
Method: Least Squares F-statistic: 3.164
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0986
Time: 04:56:49 Log-Likelihood: -73.666
No. Observations: 15 AIC: 151.3
Df Residuals: 13 BIC: 152.7
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 267.6711 98.243 2.725 0.017 55.430 479.912
expression -25.1187 14.121 -1.779 0.099 -55.625 5.388
Omnibus: 0.284 Durbin-Watson: 1.202
Prob(Omnibus): 0.868 Jarque-Bera (JB): 0.440
Skew: -0.208 Prob(JB): 0.802
Kurtosis: 2.271 Cond. No. 76.5