LID SPN TRAP

1423854_a_at

Rasl11b RAS-like, family 11, member B

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
0.001 0.981 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.664
Model: OLS Adj. R-squared: 0.611
Method: Least Squares F-statistic: 12.54
Date: Thu, 21 Nov 2024 Prob (F-statistic): 9.44e-05
Time: 03:41:20 Log-Likelihood: -100.55
No. Observations: 23 AIC: 209.1
Df Residuals: 19 BIC: 213.6
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -152.4117 308.506 -0.494 0.627 -798.123 493.299
C(dose)[T.1] 462.8908 440.298 1.051 0.306 -458.664 1384.445
expression 23.0563 34.419 0.670 0.511 -48.983 95.096
expression:C(dose)[T.1] -45.6468 49.062 -0.930 0.364 -148.335 57.041
Omnibus: 1.127 Durbin-Watson: 1.626
Prob(Omnibus): 0.569 Jarque-Bera (JB): 0.838
Skew: 0.098 Prob(JB): 0.658
Kurtosis: 2.085 Cond. No. 1.18e+03

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: 18.50
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.83e-05
Time: 03:41:20 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 48.9120 219.153 0.223 0.826 -408.234 506.057
C(dose)[T.1] 53.3244 8.786 6.070 0.000 34.998 71.651
expression 0.5910 24.445 0.024 0.981 -50.401 51.583
Omnibus: 0.320 Durbin-Watson: 1.885
Prob(Omnibus): 0.852 Jarque-Bera (JB): 0.484
Skew: 0.057 Prob(JB): 0.785
Kurtosis: 2.299 Cond. No. 455.

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: 03:41:20 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: 0.003
Model: OLS Adj. R-squared: -0.045
Method: Least Squares F-statistic: 0.05605
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.815
Time: 03:41:20 Log-Likelihood: -113.07
No. Observations: 23 AIC: 230.1
Df Residuals: 21 BIC: 232.4
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -5.5546 360.245 -0.015 0.988 -754.724 743.615
expression 9.5044 40.145 0.237 0.815 -73.981 92.990
Omnibus: 3.457 Durbin-Watson: 2.485
Prob(Omnibus): 0.178 Jarque-Bera (JB): 1.634
Skew: 0.310 Prob(JB): 0.442
Kurtosis: 1.851 Cond. No. 454.

CP101

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

F-statistic p-value df difference
3.731 0.077 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.587
Model: OLS Adj. R-squared: 0.474
Method: Least Squares F-statistic: 5.204
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0176
Time: 03:41:20 Log-Likelihood: -68.674
No. Observations: 15 AIC: 145.3
Df Residuals: 11 BIC: 148.2
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -98.0403 553.793 -0.177 0.863 -1316.931 1120.851
C(dose)[T.1] -243.6371 604.531 -0.403 0.695 -1574.200 1086.926
expression 17.4920 58.532 0.299 0.771 -111.337 146.321
expression:C(dose)[T.1] 27.5100 63.180 0.435 0.672 -111.549 166.569
Omnibus: 1.251 Durbin-Watson: 0.774
Prob(Omnibus): 0.535 Jarque-Bera (JB): 0.995
Skew: -0.562 Prob(JB): 0.608
Kurtosis: 2.426 Cond. No. 1.33e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.580
Model: OLS Adj. R-squared: 0.509
Method: Least Squares F-statistic: 8.269
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00553
Time: 03:41:20 Log-Likelihood: -68.802
No. Observations: 15 AIC: 143.6
Df Residuals: 12 BIC: 145.7
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -321.3933 201.537 -1.595 0.137 -760.504 117.717
C(dose)[T.1] 19.4227 20.653 0.940 0.366 -25.576 64.422
expression 41.1031 21.278 1.932 0.077 -5.258 87.465
Omnibus: 1.172 Durbin-Watson: 0.814
Prob(Omnibus): 0.556 Jarque-Bera (JB): 1.006
Skew: -0.501 Prob(JB): 0.605
Kurtosis: 2.222 Cond. No. 294.

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: 03:41:20 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: 0.549
Model: OLS Adj. R-squared: 0.514
Method: Least Squares F-statistic: 15.79
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00159
Time: 03:41:20 Log-Likelihood: -69.336
No. Observations: 15 AIC: 142.7
Df Residuals: 13 BIC: 144.1
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -458.0755 138.996 -3.296 0.006 -758.358 -157.793
expression 56.0372 14.100 3.974 0.002 25.576 86.498
Omnibus: 0.618 Durbin-Watson: 0.866
Prob(Omnibus): 0.734 Jarque-Bera (JB): 0.504
Skew: -0.387 Prob(JB): 0.777
Kurtosis: 2.545 Cond. No. 203.