LID SPN TRAP

1440147_at

Lgi2 leucine-rich repeat LGI family, member 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
0.483 0.495 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: 0.603
Method: Least Squares F-statistic: 12.15
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.000114
Time: 05:22:24 Log-Likelihood: -100.79
No. Observations: 23 AIC: 209.6
Df Residuals: 19 BIC: 214.1
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -61.2721 241.404 -0.254 0.802 -566.536 443.992
C(dose)[T.1] 33.7688 370.586 0.091 0.928 -741.876 809.413
expression 11.7246 24.502 0.479 0.638 -39.558 63.007
expression:C(dose)[T.1] 1.2321 36.437 0.034 0.973 -75.031 77.496
Omnibus: 0.085 Durbin-Watson: 2.215
Prob(Omnibus): 0.959 Jarque-Bera (JB): 0.308
Skew: 0.037 Prob(JB): 0.857
Kurtosis: 2.438 Cond. No. 1.08e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.657
Model: OLS Adj. R-squared: 0.623
Method: Least Squares F-statistic: 19.18
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.23e-05
Time: 05:22:24 Log-Likelihood: -100.79
No. Observations: 23 AIC: 207.6
Df Residuals: 20 BIC: 211.0
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -66.7595 174.204 -0.383 0.706 -430.142 296.623
C(dose)[T.1] 46.2917 13.339 3.471 0.002 18.468 74.115
expression 12.2817 17.676 0.695 0.495 -24.590 49.154
Omnibus: 0.092 Durbin-Watson: 2.221
Prob(Omnibus): 0.955 Jarque-Bera (JB): 0.316
Skew: 0.038 Prob(JB): 0.854
Kurtosis: 2.431 Cond. No. 413.

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: 05:22:24 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: 0.451
Model: OLS Adj. R-squared: 0.425
Method: Least Squares F-statistic: 17.25
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.000451
Time: 05:22:24 Log-Likelihood: -106.21
No. Observations: 23 AIC: 216.4
Df Residuals: 21 BIC: 218.7
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -516.7442 143.716 -3.596 0.002 -815.618 -217.870
expression 58.9170 14.186 4.153 0.000 29.415 88.419
Omnibus: 3.131 Durbin-Watson: 2.934
Prob(Omnibus): 0.209 Jarque-Bera (JB): 1.364
Skew: 0.147 Prob(JB): 0.506
Kurtosis: 1.843 Cond. No. 275.

CP101

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

F-statistic p-value df difference
3.873 0.073 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.610
Model: OLS Adj. R-squared: 0.503
Method: Least Squares F-statistic: 5.725
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0131
Time: 05:22:24 Log-Likelihood: -68.246
No. Observations: 15 AIC: 144.5
Df Residuals: 11 BIC: 147.3
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -184.3532 382.971 -0.481 0.640 -1027.268 658.561
C(dose)[T.1] -412.7932 520.638 -0.793 0.445 -1558.709 733.122
expression 23.8514 36.266 0.658 0.524 -55.971 103.673
expression:C(dose)[T.1] 41.9190 48.690 0.861 0.408 -65.247 149.085
Omnibus: 2.637 Durbin-Watson: 0.650
Prob(Omnibus): 0.268 Jarque-Bera (JB): 1.719
Skew: -0.817 Prob(JB): 0.423
Kurtosis: 2.715 Cond. No. 1.11e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.583
Model: OLS Adj. R-squared: 0.514
Method: Least Squares F-statistic: 8.398
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00524
Time: 05:22:24 Log-Likelihood: -68.735
No. Observations: 15 AIC: 143.5
Df Residuals: 12 BIC: 145.6
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -429.8543 252.872 -1.700 0.115 -980.815 121.107
C(dose)[T.1] 35.2430 15.413 2.287 0.041 1.662 68.824
expression 47.1079 23.936 1.968 0.073 -5.044 99.260
Omnibus: 2.218 Durbin-Watson: 0.691
Prob(Omnibus): 0.330 Jarque-Bera (JB): 1.446
Skew: -0.535 Prob(JB): 0.485
Kurtosis: 1.919 Cond. No. 401.

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: 05:22:24 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: 0.402
Model: OLS Adj. R-squared: 0.356
Method: Least Squares F-statistic: 8.728
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0112
Time: 05:22:24 Log-Likelihood: -71.448
No. Observations: 15 AIC: 146.9
Df Residuals: 13 BIC: 148.3
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -680.8111 262.262 -2.596 0.022 -1247.393 -114.230
expression 72.2849 24.467 2.954 0.011 19.427 125.142
Omnibus: 1.351 Durbin-Watson: 1.270
Prob(Omnibus): 0.509 Jarque-Bera (JB): 0.848
Skew: -0.182 Prob(JB): 0.654
Kurtosis: 1.893 Cond. No. 361.