LID SPN TRAP

1460645_at

Chordc1 cysteine and histidine-rich domain (CHORD)-containing, zinc-binding protein 1

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
0.792 0.384 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.674
Model: OLS Adj. R-squared: 0.623
Method: Least Squares F-statistic: 13.10
Date: Thu, 03 Apr 2025 Prob (F-statistic): 7.20e-05
Time: 22:58:22 Log-Likelihood: -100.21
No. Observations: 23 AIC: 208.4
Df Residuals: 19 BIC: 213.0
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 118.3936 341.345 0.347 0.733 -596.049 832.836
C(dose)[T.1] 509.8677 554.505 0.920 0.369 -650.725 1670.460
expression -6.4905 34.512 -0.188 0.853 -78.725 65.744
expression:C(dose)[T.1] -46.0568 55.994 -0.823 0.421 -163.253 71.140
Omnibus: 0.095 Durbin-Watson: 1.904
Prob(Omnibus): 0.953 Jarque-Bera (JB): 0.043
Skew: 0.030 Prob(JB): 0.979
Kurtosis: 2.796 Cond. No. 1.58e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.662
Model: OLS Adj. R-squared: 0.629
Method: Least Squares F-statistic: 19.62
Date: Thu, 03 Apr 2025 Prob (F-statistic): 1.92e-05
Time: 22:58:22 Log-Likelihood: -100.62
No. Observations: 23 AIC: 207.2
Df Residuals: 20 BIC: 210.6
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 291.4179 266.642 1.093 0.287 -264.787 847.623
C(dose)[T.1] 53.8258 8.619 6.245 0.000 35.847 71.804
expression -23.9870 26.957 -0.890 0.384 -80.217 32.243
Omnibus: 0.050 Durbin-Watson: 1.950
Prob(Omnibus): 0.975 Jarque-Bera (JB): 0.239
Skew: 0.080 Prob(JB): 0.887
Kurtosis: 2.527 Cond. No. 621.

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: 22:58:22 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: 0.004
Model: OLS Adj. R-squared: -0.043
Method: Least Squares F-statistic: 0.08648
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.772
Time: 22:58:23 Log-Likelihood: -113.06
No. Observations: 23 AIC: 230.1
Df Residuals: 21 BIC: 232.4
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 210.9832 446.423 0.473 0.641 -717.404 1139.371
expression -13.2607 45.093 -0.294 0.772 -107.036 80.515
Omnibus: 3.759 Durbin-Watson: 2.544
Prob(Omnibus): 0.153 Jarque-Bera (JB): 1.621
Skew: 0.267 Prob(JB): 0.445
Kurtosis: 1.814 Cond. No. 620.

CP101

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

F-statistic p-value df difference
0.202 0.661 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.483
Model: OLS Adj. R-squared: 0.342
Method: Least Squares F-statistic: 3.421
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.0563
Time: 22:58:23 Log-Likelihood: -70.357
No. Observations: 15 AIC: 148.7
Df Residuals: 11 BIC: 151.5
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -385.1432 555.250 -0.694 0.502 -1607.241 836.954
C(dose)[T.1] 647.3345 830.770 0.779 0.452 -1181.178 2475.847
expression 45.9102 56.314 0.815 0.432 -78.036 169.856
expression:C(dose)[T.1] -60.3415 83.207 -0.725 0.483 -243.478 122.795
Omnibus: 2.226 Durbin-Watson: 0.893
Prob(Omnibus): 0.329 Jarque-Bera (JB): 1.373
Skew: -0.732 Prob(JB): 0.503
Kurtosis: 2.768 Cond. No. 1.38e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.458
Model: OLS Adj. R-squared: 0.368
Method: Least Squares F-statistic: 5.068
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.0254
Time: 22:58:23 Log-Likelihood: -70.708
No. Observations: 15 AIC: 147.4
Df Residuals: 12 BIC: 149.5
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -112.6802 400.678 -0.281 0.783 -985.683 760.323
C(dose)[T.1] 45.0107 18.173 2.477 0.029 5.415 84.607
expression 18.2708 40.630 0.450 0.661 -70.253 106.795
Omnibus: 2.362 Durbin-Watson: 0.787
Prob(Omnibus): 0.307 Jarque-Bera (JB): 1.738
Skew: -0.789 Prob(JB): 0.419
Kurtosis: 2.463 Cond. No. 520.

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: 22:58:23 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: 0.181
Model: OLS Adj. R-squared: 0.118
Method: Least Squares F-statistic: 2.869
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.114
Time: 22:58:23 Log-Likelihood: -73.804
No. Observations: 15 AIC: 151.6
Df Residuals: 13 BIC: 153.0
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -603.0402 411.424 -1.466 0.166 -1491.868 285.788
expression 69.8107 41.215 1.694 0.114 -19.228 158.850
Omnibus: 2.780 Durbin-Watson: 1.690
Prob(Omnibus): 0.249 Jarque-Bera (JB): 1.245
Skew: 0.298 Prob(JB): 0.537
Kurtosis: 1.720 Cond. No. 451.