LID SPN TRAP

1455269_a_at

Coro1a coronin, actin binding protein 1A

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
1.426 0.246 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.740
Model: OLS Adj. R-squared: 0.699
Method: Least Squares F-statistic: 18.04
Date: Thu, 03 Apr 2025 Prob (F-statistic): 8.69e-06
Time: 23:00:40 Log-Likelihood: -97.605
No. Observations: 23 AIC: 203.2
Df Residuals: 19 BIC: 207.8
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 70.4494 248.060 0.284 0.779 -448.746 589.645
C(dose)[T.1] 1207.2778 516.871 2.336 0.031 125.454 2289.101
expression -1.5217 23.237 -0.065 0.948 -50.157 47.113
expression:C(dose)[T.1] -106.8522 47.993 -2.226 0.038 -207.303 -6.402
Omnibus: 1.653 Durbin-Watson: 1.918
Prob(Omnibus): 0.438 Jarque-Bera (JB): 1.435
Skew: 0.492 Prob(JB): 0.488
Kurtosis: 2.272 Cond. No. 1.70e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.672
Model: OLS Adj. R-squared: 0.640
Method: Least Squares F-statistic: 20.53
Date: Thu, 03 Apr 2025 Prob (F-statistic): 1.42e-05
Time: 23:00:40 Log-Likelihood: -100.27
No. Observations: 23 AIC: 206.5
Df Residuals: 20 BIC: 209.9
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 337.7856 237.566 1.422 0.170 -157.768 833.339
C(dose)[T.1] 56.6517 8.916 6.354 0.000 38.053 75.251
expression -26.5699 22.252 -1.194 0.246 -72.987 19.847
Omnibus: 2.200 Durbin-Watson: 2.140
Prob(Omnibus): 0.333 Jarque-Bera (JB): 1.142
Skew: 0.111 Prob(JB): 0.565
Kurtosis: 1.931 Cond. No. 608.

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: 23:00:40 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: 0.011
Model: OLS Adj. R-squared: -0.036
Method: Least Squares F-statistic: 0.2368
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.632
Time: 23:00:40 Log-Likelihood: -112.98
No. Observations: 23 AIC: 230.0
Df Residuals: 21 BIC: 232.2
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -107.5504 384.869 -0.279 0.783 -907.929 692.828
expression 17.4486 35.854 0.487 0.632 -57.113 92.011
Omnibus: 2.701 Durbin-Watson: 2.373
Prob(Omnibus): 0.259 Jarque-Bera (JB): 1.488
Skew: 0.319 Prob(JB): 0.475
Kurtosis: 1.930 Cond. No. 581.

CP101

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

F-statistic p-value df difference
10.606 0.007 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.714
Model: OLS Adj. R-squared: 0.637
Method: Least Squares F-statistic: 9.175
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.00249
Time: 23:00:40 Log-Likelihood: -65.899
No. Observations: 15 AIC: 139.8
Df Residuals: 11 BIC: 142.6
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -548.1891 338.881 -1.618 0.134 -1294.062 197.684
C(dose)[T.1] -200.1063 472.012 -0.424 0.680 -1238.998 838.785
expression 59.2009 32.578 1.817 0.097 -12.503 130.904
expression:C(dose)[T.1] 23.6596 45.294 0.522 0.612 -76.031 123.350
Omnibus: 0.140 Durbin-Watson: 1.540
Prob(Omnibus): 0.932 Jarque-Bera (JB): 0.103
Skew: -0.118 Prob(JB): 0.950
Kurtosis: 2.670 Cond. No. 1.13e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.707
Model: OLS Adj. R-squared: 0.659
Method: Least Squares F-statistic: 14.51
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.000628
Time: 23:00:40 Log-Likelihood: -66.083
No. Observations: 15 AIC: 138.2
Df Residuals: 12 BIC: 140.3
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -675.4695 228.270 -2.959 0.012 -1172.827 -178.112
C(dose)[T.1] 46.3757 11.500 4.033 0.002 21.319 71.433
expression 71.4408 21.937 3.257 0.007 23.645 119.237
Omnibus: 0.040 Durbin-Watson: 1.559
Prob(Omnibus): 0.980 Jarque-Bera (JB): 0.229
Skew: -0.092 Prob(JB): 0.892
Kurtosis: 2.423 Cond. No. 420.

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: 23:00:40 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: 0.311
Model: OLS Adj. R-squared: 0.258
Method: Least Squares F-statistic: 5.864
Date: Thu, 03 Apr 2025 Prob (F-statistic): 0.0308
Time: 23:00:41 Log-Likelihood: -72.508
No. Observations: 15 AIC: 149.0
Df Residuals: 13 BIC: 150.4
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -720.1583 336.172 -2.142 0.052 -1446.414 6.098
expression 78.1033 32.252 2.422 0.031 8.426 147.781
Omnibus: 0.859 Durbin-Watson: 2.298
Prob(Omnibus): 0.651 Jarque-Bera (JB): 0.783
Skew: 0.341 Prob(JB): 0.676
Kurtosis: 2.113 Cond. No. 419.