LID SPN TRAP

1460555_at

Fam65b family with sequence similarity 65, 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 0.975 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.675
Model: OLS Adj. R-squared: 0.623
Method: Least Squares F-statistic: 13.13
Date: Thu, 21 Nov 2024 Prob (F-statistic): 7.09e-05
Time: 04:56:01 Log-Likelihood: -100.20
No. Observations: 23 AIC: 208.4
Df Residuals: 19 BIC: 212.9
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -25.8262 155.419 -0.166 0.870 -351.122 299.470
C(dose)[T.1] 544.9493 403.415 1.351 0.193 -299.408 1389.307
expression 9.0525 17.566 0.515 0.612 -27.714 45.819
expression:C(dose)[T.1] -53.7214 44.051 -1.220 0.238 -145.922 38.479
Omnibus: 0.261 Durbin-Watson: 1.711
Prob(Omnibus): 0.878 Jarque-Bera (JB): 0.294
Skew: -0.214 Prob(JB): 0.863
Kurtosis: 2.649 Cond. No. 986.

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: 04:56:01 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 49.6973 144.274 0.344 0.734 -251.252 350.647
C(dose)[T.1] 53.1469 10.671 4.981 0.000 30.888 75.405
expression 0.5102 16.304 0.031 0.975 -33.499 34.520
Omnibus: 0.318 Durbin-Watson: 1.891
Prob(Omnibus): 0.853 Jarque-Bera (JB): 0.483
Skew: 0.064 Prob(JB): 0.785
Kurtosis: 2.301 Cond. No. 302.

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: 04:56:01 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: 0.214
Model: OLS Adj. R-squared: 0.176
Method: Least Squares F-statistic: 5.711
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0263
Time: 04:56:01 Log-Likelihood: -110.34
No. Observations: 23 AIC: 224.7
Df Residuals: 21 BIC: 226.9
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -342.1513 176.652 -1.937 0.066 -709.518 25.216
expression 46.7732 19.573 2.390 0.026 6.069 87.477
Omnibus: 0.646 Durbin-Watson: 2.535
Prob(Omnibus): 0.724 Jarque-Bera (JB): 0.397
Skew: 0.310 Prob(JB): 0.820
Kurtosis: 2.828 Cond. No. 252.

CP101

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

F-statistic p-value df difference
5.104 0.043 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.660
Model: OLS Adj. R-squared: 0.567
Method: Least Squares F-statistic: 7.120
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00630
Time: 04:56:01 Log-Likelihood: -67.208
No. Observations: 15 AIC: 142.4
Df Residuals: 11 BIC: 145.2
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 410.8910 428.896 0.958 0.359 -533.102 1354.884
C(dose)[T.1] 849.0794 628.515 1.351 0.204 -534.274 2232.432
expression -42.0836 52.539 -0.801 0.440 -157.721 73.554
expression:C(dose)[T.1] -92.9386 75.518 -1.231 0.244 -259.153 73.276
Omnibus: 0.368 Durbin-Watson: 1.236
Prob(Omnibus): 0.832 Jarque-Bera (JB): 0.202
Skew: -0.246 Prob(JB): 0.904
Kurtosis: 2.715 Cond. No. 1.09e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.613
Model: OLS Adj. R-squared: 0.549
Method: Least Squares F-statistic: 9.514
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00335
Time: 04:56:01 Log-Likelihood: -68.175
No. Observations: 15 AIC: 142.4
Df Residuals: 12 BIC: 144.5
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 778.0209 314.693 2.472 0.029 92.364 1463.678
C(dose)[T.1] 75.8735 17.699 4.287 0.001 37.310 114.437
expression -87.0671 38.540 -2.259 0.043 -171.040 -3.095
Omnibus: 0.855 Durbin-Watson: 1.368
Prob(Omnibus): 0.652 Jarque-Bera (JB): 0.782
Skew: -0.448 Prob(JB): 0.676
Kurtosis: 2.331 Cond. No. 405.

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: 04:56:02 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: 0.021
Model: OLS Adj. R-squared: -0.054
Method: Least Squares F-statistic: 0.2786
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.606
Time: 04:56:02 Log-Likelihood: -75.141
No. Observations: 15 AIC: 154.3
Df Residuals: 13 BIC: 155.7
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -99.1735 365.468 -0.271 0.790 -888.719 690.372
expression 23.1644 43.884 0.528 0.606 -71.642 117.971
Omnibus: 0.893 Durbin-Watson: 1.291
Prob(Omnibus): 0.640 Jarque-Bera (JB): 0.675
Skew: 0.009 Prob(JB): 0.713
Kurtosis: 1.961 Cond. No. 307.