LID SPN TRAP

1455324_at

Plcxd2 phosphatidylinositol-specific phospholipase C, X domain containing 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
0.110 0.744 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.683
Model: OLS Adj. R-squared: 0.633
Method: Least Squares F-statistic: 13.67
Date: Thu, 21 Nov 2024 Prob (F-statistic): 5.48e-05
Time: 05:24:32 Log-Likelihood: -99.878
No. Observations: 23 AIC: 207.8
Df Residuals: 19 BIC: 212.3
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 106.4145 72.117 1.476 0.156 -44.529 257.358
C(dose)[T.1] -90.1114 103.265 -0.873 0.394 -306.247 126.024
expression -8.0920 11.141 -0.726 0.476 -31.410 15.226
expression:C(dose)[T.1] 22.3607 16.024 1.395 0.179 -11.178 55.900
Omnibus: 0.914 Durbin-Watson: 1.876
Prob(Omnibus): 0.633 Jarque-Bera (JB): 0.504
Skew: 0.360 Prob(JB): 0.777
Kurtosis: 2.911 Cond. No. 205.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.651
Model: OLS Adj. R-squared: 0.616
Method: Least Squares F-statistic: 18.65
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.68e-05
Time: 05:24:32 Log-Likelihood: -101.00
No. Observations: 23 AIC: 208.0
Df Residuals: 20 BIC: 211.4
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 36.6843 53.216 0.689 0.499 -74.322 147.691
C(dose)[T.1] 53.4918 8.758 6.108 0.000 35.222 71.761
expression 2.7163 8.195 0.331 0.744 -14.378 19.811
Omnibus: 0.321 Durbin-Watson: 1.880
Prob(Omnibus): 0.852 Jarque-Bera (JB): 0.488
Skew: 0.100 Prob(JB): 0.784
Kurtosis: 2.315 Cond. No. 80.6

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: 05:24:32 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: -0.048
Method: Least Squares F-statistic: 1.329e-05
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.997
Time: 05:24:32 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 79.4009 87.143 0.911 0.373 -101.824 260.625
expression 0.0493 13.518 0.004 0.997 -28.063 28.162
Omnibus: 3.308 Durbin-Watson: 2.490
Prob(Omnibus): 0.191 Jarque-Bera (JB): 1.569
Skew: 0.289 Prob(JB): 0.456
Kurtosis: 1.858 Cond. No. 79.7

CP101

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

F-statistic p-value df difference
0.026 0.874 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.569
Model: OLS Adj. R-squared: 0.451
Method: Least Squares F-statistic: 4.835
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0220
Time: 05:24:32 Log-Likelihood: -68.992
No. Observations: 15 AIC: 146.0
Df Residuals: 11 BIC: 148.8
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 194.9863 108.232 1.802 0.099 -43.231 433.204
C(dose)[T.1] -195.8074 141.903 -1.380 0.195 -508.134 116.519
expression -20.9755 17.712 -1.184 0.261 -59.959 18.008
expression:C(dose)[T.1] 41.2373 23.695 1.740 0.110 -10.915 93.389
Omnibus: 2.081 Durbin-Watson: 1.281
Prob(Omnibus): 0.353 Jarque-Bera (JB): 1.305
Skew: -0.710 Prob(JB): 0.521
Kurtosis: 2.735 Cond. No. 164.

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: 4.909
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0277
Time: 05:24:32 Log-Likelihood: -70.817
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 54.8655 78.208 0.702 0.496 -115.535 225.266
C(dose)[T.1] 49.7849 16.135 3.086 0.009 14.631 84.939
expression 2.0659 12.721 0.162 0.874 -25.651 29.783
Omnibus: 2.686 Durbin-Watson: 0.796
Prob(Omnibus): 0.261 Jarque-Bera (JB): 1.831
Skew: -0.837 Prob(JB): 0.400
Kurtosis: 2.638 Cond. No. 61.4

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: 05:24:32 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: 0.014
Model: OLS Adj. R-squared: -0.062
Method: Least Squares F-statistic: 0.1791
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.679
Time: 05:24:33 Log-Likelihood: -75.197
No. Observations: 15 AIC: 154.4
Df Residuals: 13 BIC: 155.8
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 133.6898 95.106 1.406 0.183 -71.775 339.155
expression -6.7500 15.949 -0.423 0.679 -41.207 27.707
Omnibus: 1.474 Durbin-Watson: 1.636
Prob(Omnibus): 0.479 Jarque-Bera (JB): 0.873
Skew: 0.168 Prob(JB): 0.646
Kurtosis: 1.867 Cond. No. 57.8