LID SPN TRAP

1422821_s_at

Stard5 StAR-related lipid transfer (START) domain containing 5

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
0.010 0.920 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.650
Model: OLS Adj. R-squared: 0.594
Method: Least Squares F-statistic: 11.74
Date: Tue, 28 Jan 2025 Prob (F-statistic): 0.000141
Time: 19:14:49 Log-Likelihood: -101.04
No. Observations: 23 AIC: 210.1
Df Residuals: 19 BIC: 214.6
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 55.0322 49.846 1.104 0.283 -49.297 159.362
C(dose)[T.1] 66.7096 95.582 0.698 0.494 -133.345 266.765
expression -0.1601 9.611 -0.017 0.987 -20.276 19.956
expression:C(dose)[T.1] -2.8677 19.824 -0.145 0.887 -44.361 38.625
Omnibus: 0.311 Durbin-Watson: 1.846
Prob(Omnibus): 0.856 Jarque-Bera (JB): 0.477
Skew: 0.031 Prob(JB): 0.788
Kurtosis: 2.297 Cond. No. 127.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.649
Model: OLS Adj. R-squared: 0.614
Method: Least Squares F-statistic: 18.51
Date: Tue, 28 Jan 2025 Prob (F-statistic): 2.82e-05
Time: 19:14:50 Log-Likelihood: -101.06
No. Observations: 23 AIC: 208.1
Df Residuals: 20 BIC: 211.5
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 58.5006 42.618 1.373 0.185 -30.398 147.399
C(dose)[T.1] 52.9557 9.535 5.554 0.000 33.066 72.846
expression -0.8341 8.198 -0.102 0.920 -17.934 16.266
Omnibus: 0.284 Durbin-Watson: 1.873
Prob(Omnibus): 0.868 Jarque-Bera (JB): 0.461
Skew: 0.040 Prob(JB): 0.794
Kurtosis: 2.311 Cond. No. 50.6

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: Tue, 28 Jan 2025 Prob (F-statistic): 3.51e-06
Time: 19:14:50 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: 0.108
Model: OLS Adj. R-squared: 0.066
Method: Least Squares F-statistic: 2.550
Date: Tue, 28 Jan 2025 Prob (F-statistic): 0.125
Time: 19:14:50 Log-Likelihood: -111.79
No. Observations: 23 AIC: 227.6
Df Residuals: 21 BIC: 229.8
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 172.0085 58.190 2.956 0.008 50.996 293.021
expression -18.7309 11.729 -1.597 0.125 -43.122 5.660
Omnibus: 0.524 Durbin-Watson: 2.201
Prob(Omnibus): 0.770 Jarque-Bera (JB): 0.587
Skew: 0.004 Prob(JB): 0.746
Kurtosis: 2.217 Cond. No. 44.1

CP101

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

F-statistic p-value df difference
2.587 0.134 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.576
Model: OLS Adj. R-squared: 0.460
Method: Least Squares F-statistic: 4.980
Date: Tue, 28 Jan 2025 Prob (F-statistic): 0.0202
Time: 19:14:50 Log-Likelihood: -68.866
No. Observations: 15 AIC: 145.7
Df Residuals: 11 BIC: 148.6
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -24.1373 338.907 -0.071 0.945 -770.066 721.792
C(dose)[T.1] 359.9200 360.344 0.999 0.339 -433.191 1153.031
expression 18.6434 68.970 0.270 0.792 -133.159 170.446
expression:C(dose)[T.1] -64.1724 73.482 -0.873 0.401 -225.905 97.561
Omnibus: 0.616 Durbin-Watson: 0.976
Prob(Omnibus): 0.735 Jarque-Bera (JB): 0.405
Skew: -0.365 Prob(JB): 0.817
Kurtosis: 2.661 Cond. No. 398.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.547
Model: OLS Adj. R-squared: 0.471
Method: Least Squares F-statistic: 7.231
Date: Tue, 28 Jan 2025 Prob (F-statistic): 0.00870
Time: 19:14:50 Log-Likelihood: -69.369
No. Observations: 15 AIC: 144.7
Df Residuals: 12 BIC: 146.9
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 253.5247 116.179 2.182 0.050 0.393 506.656
C(dose)[T.1] 45.4882 14.461 3.146 0.008 13.980 76.996
expression -37.8903 23.559 -1.608 0.134 -89.221 13.441
Omnibus: 0.662 Durbin-Watson: 1.058
Prob(Omnibus): 0.718 Jarque-Bera (JB): 0.678
Skew: -0.364 Prob(JB): 0.712
Kurtosis: 2.254 Cond. No. 83.2

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: 19:14:50 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: 0.173
Model: OLS Adj. R-squared: 0.109
Method: Least Squares F-statistic: 2.712
Date: Tue, 28 Jan 2025 Prob (F-statistic): 0.124
Time: 19:14:50 Log-Likelihood: -73.879
No. Observations: 15 AIC: 151.8
Df Residuals: 13 BIC: 153.2
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 335.2012 146.959 2.281 0.040 17.716 652.687
expression -49.7061 30.183 -1.647 0.124 -114.913 15.501
Omnibus: 0.165 Durbin-Watson: 1.721
Prob(Omnibus): 0.921 Jarque-Bera (JB): 0.046
Skew: 0.053 Prob(JB): 0.977
Kurtosis: 2.749 Cond. No. 80.7