LID SPN TRAP

1457651_x_at

Rem2 rad and gem related GTP binding protein 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
0.217 0.647 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.670
Model: OLS Adj. R-squared: 0.618
Method: Least Squares F-statistic: 12.85
Date: Thu, 21 Nov 2024 Prob (F-statistic): 8.10e-05
Time: 03:55:48 Log-Likelihood: -100.36
No. Observations: 23 AIC: 208.7
Df Residuals: 19 BIC: 213.3
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -119.1691 479.659 -0.248 0.806 -1123.107 884.768
C(dose)[T.1] 730.6579 684.362 1.068 0.299 -701.729 2163.045
expression 15.2254 42.119 0.361 0.722 -72.930 103.381
expression:C(dose)[T.1] -59.5166 60.119 -0.990 0.335 -185.346 66.313
Omnibus: 0.134 Durbin-Watson: 1.783
Prob(Omnibus): 0.935 Jarque-Bera (JB): 0.284
Skew: 0.151 Prob(JB): 0.868
Kurtosis: 2.547 Cond. No. 2.33e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.653
Model: OLS Adj. R-squared: 0.618
Method: Least Squares F-statistic: 18.80
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.54e-05
Time: 03:55:48 Log-Likelihood: -100.94
No. Observations: 23 AIC: 207.9
Df Residuals: 20 BIC: 211.3
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 213.4831 342.123 0.624 0.540 -500.172 927.139
C(dose)[T.1] 53.2052 8.727 6.096 0.000 35.000 71.410
expression -13.9869 30.039 -0.466 0.647 -76.648 48.674
Omnibus: 0.537 Durbin-Watson: 1.848
Prob(Omnibus): 0.764 Jarque-Bera (JB): 0.594
Skew: -0.029 Prob(JB): 0.743
Kurtosis: 2.215 Cond. No. 902.

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: 03:55:48 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: 0.008
Model: OLS Adj. R-squared: -0.040
Method: Least Squares F-statistic: 0.1619
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.691
Time: 03:55:48 Log-Likelihood: -113.02
No. Observations: 23 AIC: 230.0
Df Residuals: 21 BIC: 232.3
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 306.6072 563.909 0.544 0.592 -866.105 1479.319
expression -19.9325 49.536 -0.402 0.691 -122.948 83.083
Omnibus: 2.604 Durbin-Watson: 2.442
Prob(Omnibus): 0.272 Jarque-Bera (JB): 1.315
Skew: 0.209 Prob(JB): 0.518
Kurtosis: 1.906 Cond. No. 900.

CP101

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

F-statistic p-value df difference
0.482 0.501 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.524
Model: OLS Adj. R-squared: 0.394
Method: Least Squares F-statistic: 4.029
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0369
Time: 03:55:48 Log-Likelihood: -69.740
No. Observations: 15 AIC: 147.5
Df Residuals: 11 BIC: 150.3
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 228.6830 962.872 0.238 0.817 -1890.583 2347.949
C(dose)[T.1] -1632.3606 1512.625 -1.079 0.304 -4961.626 1696.905
expression -14.0925 84.143 -0.167 0.870 -199.289 171.104
expression:C(dose)[T.1] 146.8808 132.141 1.112 0.290 -143.961 437.722
Omnibus: 0.822 Durbin-Watson: 0.967
Prob(Omnibus): 0.663 Jarque-Bera (JB): 0.759
Skew: -0.327 Prob(JB): 0.684
Kurtosis: 2.113 Cond. No. 2.92e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.470
Model: OLS Adj. R-squared: 0.382
Method: Least Squares F-statistic: 5.322
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0222
Time: 03:55:48 Log-Likelihood: -70.538
No. Observations: 15 AIC: 147.1
Df Residuals: 12 BIC: 149.2
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -452.7802 749.717 -0.604 0.557 -2086.273 1180.712
C(dose)[T.1] 48.8996 15.439 3.167 0.008 15.261 82.538
expression 45.4627 65.513 0.694 0.501 -97.277 188.203
Omnibus: 1.464 Durbin-Watson: 0.837
Prob(Omnibus): 0.481 Jarque-Bera (JB): 1.180
Skew: -0.534 Prob(JB): 0.554
Kurtosis: 2.135 Cond. No. 1.12e+03

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: 03:55:48 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: 0.027
Model: OLS Adj. R-squared: -0.048
Method: Least Squares F-statistic: 0.3608
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.558
Time: 03:55:48 Log-Likelihood: -75.095
No. Observations: 15 AIC: 154.2
Df Residuals: 13 BIC: 155.6
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -492.5026 975.863 -0.505 0.622 -2600.727 1615.722
expression 51.2116 85.253 0.601 0.558 -132.967 235.390
Omnibus: 0.459 Durbin-Watson: 1.623
Prob(Omnibus): 0.795 Jarque-Bera (JB): 0.526
Skew: 0.063 Prob(JB): 0.769
Kurtosis: 2.091 Cond. No. 1.12e+03