LID SPN TRAP

1426865_a_at

Ncam1 neural cell adhesion molecule 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
0.998 0.330 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.667
Model: OLS Adj. R-squared: 0.614
Method: Least Squares F-statistic: 12.68
Date: Tue, 28 Jan 2025 Prob (F-statistic): 8.79e-05
Time: 18:56:13 Log-Likelihood: -100.46
No. Observations: 23 AIC: 208.9
Df Residuals: 19 BIC: 213.5
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 433.6463 526.819 0.823 0.421 -668.999 1536.292
C(dose)[T.1] -106.3015 611.644 -0.174 0.864 -1386.488 1173.885
expression -39.1469 54.349 -0.720 0.480 -152.900 74.606
expression:C(dose)[T.1] 16.4821 63.089 0.261 0.797 -115.564 148.528
Omnibus: 2.171 Durbin-Watson: 2.009
Prob(Omnibus): 0.338 Jarque-Bera (JB): 1.107
Skew: -0.030 Prob(JB): 0.575
Kurtosis: 1.927 Cond. No. 1.98e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.666
Model: OLS Adj. R-squared: 0.632
Method: Least Squares F-statistic: 19.92
Date: Tue, 28 Jan 2025 Prob (F-statistic): 1.74e-05
Time: 18:56:13 Log-Likelihood: -100.50
No. Observations: 23 AIC: 207.0
Df Residuals: 20 BIC: 210.4
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 315.0882 261.271 1.206 0.242 -229.913 860.090
C(dose)[T.1] 53.4756 8.560 6.247 0.000 35.619 71.332
expression -26.9152 26.949 -0.999 0.330 -83.129 29.299
Omnibus: 2.075 Durbin-Watson: 1.964
Prob(Omnibus): 0.354 Jarque-Bera (JB): 1.083
Skew: 0.027 Prob(JB): 0.582
Kurtosis: 1.938 Cond. No. 600.

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: Tue, 28 Jan 2025 Prob (F-statistic): 3.51e-06
Time: 18:56:13 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: 0.013
Model: OLS Adj. R-squared: -0.034
Method: Least Squares F-statistic: 0.2867
Date: Tue, 28 Jan 2025 Prob (F-statistic): 0.598
Time: 18:56:13 Log-Likelihood: -112.95
No. Observations: 23 AIC: 229.9
Df Residuals: 21 BIC: 232.2
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 314.2343 438.028 0.717 0.481 -596.695 1225.164
expression -24.1892 45.174 -0.535 0.598 -118.134 69.756
Omnibus: 3.087 Durbin-Watson: 2.525
Prob(Omnibus): 0.214 Jarque-Bera (JB): 1.520
Skew: 0.286 Prob(JB): 0.468
Kurtosis: 1.878 Cond. No. 599.

CP101

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

F-statistic p-value df difference
0.027 0.872 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.577
Model: OLS Adj. R-squared: 0.462
Method: Least Squares F-statistic: 5.004
Date: Tue, 28 Jan 2025 Prob (F-statistic): 0.0199
Time: 18:56:13 Log-Likelihood: -68.845
No. Observations: 15 AIC: 145.7
Df Residuals: 11 BIC: 148.5
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -524.9171 393.725 -1.333 0.209 -1391.500 341.666
C(dose)[T.1] 867.5051 450.220 1.927 0.080 -123.423 1858.433
expression 66.9662 44.496 1.505 0.160 -30.968 164.901
expression:C(dose)[T.1] -92.3883 50.815 -1.818 0.096 -204.231 19.454
Omnibus: 3.091 Durbin-Watson: 1.021
Prob(Omnibus): 0.213 Jarque-Bera (JB): 1.308
Skew: -0.693 Prob(JB): 0.520
Kurtosis: 3.413 Cond. No. 843.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.450
Model: OLS Adj. R-squared: 0.358
Method: Least Squares F-statistic: 4.910
Date: Tue, 28 Jan 2025 Prob (F-statistic): 0.0277
Time: 18:56:13 Log-Likelihood: -70.816
No. Observations: 15 AIC: 147.6
Df Residuals: 12 BIC: 149.8
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 101.6870 207.860 0.489 0.634 -351.201 554.575
C(dose)[T.1] 49.3629 15.754 3.133 0.009 15.038 83.688
expression -3.8730 23.463 -0.165 0.872 -54.995 47.249
Omnibus: 2.846 Durbin-Watson: 0.841
Prob(Omnibus): 0.241 Jarque-Bera (JB): 1.902
Skew: -0.858 Prob(JB): 0.386
Kurtosis: 2.685 Cond. No. 239.

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: Tue, 28 Jan 2025 Prob (F-statistic): 0.00629
Time: 18:56:13 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: 0.000
Model: OLS Adj. R-squared: -0.077
Method: Least Squares F-statistic: 0.0007546
Date: Tue, 28 Jan 2025 Prob (F-statistic): 0.979
Time: 18:56:13 Log-Likelihood: -75.300
No. Observations: 15 AIC: 154.6
Df Residuals: 13 BIC: 156.0
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 86.2766 269.205 0.320 0.754 -495.305 667.859
expression 0.8333 30.334 0.027 0.979 -64.699 66.366
Omnibus: 0.637 Durbin-Watson: 1.618
Prob(Omnibus): 0.727 Jarque-Bera (JB): 0.594
Skew: 0.056 Prob(JB): 0.743
Kurtosis: 2.031 Cond. No. 238.