LID SPN TRAP

1450724_at

Fam126a family with sequence similarity 126, member A

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
2.061 0.167 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.700
Model: OLS Adj. R-squared: 0.653
Method: Least Squares F-statistic: 14.77
Date: Thu, 21 Nov 2024 Prob (F-statistic): 3.33e-05
Time: 04:27:49 Log-Likelihood: -99.261
No. Observations: 23 AIC: 206.5
Df Residuals: 19 BIC: 211.1
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 91.9251 127.532 0.721 0.480 -175.003 358.854
C(dose)[T.1] -81.9377 139.054 -0.589 0.563 -372.981 209.106
expression -5.6771 19.176 -0.296 0.770 -45.814 34.460
expression:C(dose)[T.1] 23.0801 21.548 1.071 0.298 -22.021 68.181
Omnibus: 0.205 Durbin-Watson: 1.792
Prob(Omnibus): 0.902 Jarque-Bera (JB): 0.375
Skew: 0.170 Prob(JB): 0.829
Kurtosis: 2.476 Cond. No. 309.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.682
Model: OLS Adj. R-squared: 0.650
Method: Least Squares F-statistic: 21.43
Date: Thu, 21 Nov 2024 Prob (F-statistic): 1.06e-05
Time: 04:27:49 Log-Likelihood: -99.935
No. Observations: 23 AIC: 205.9
Df Residuals: 20 BIC: 209.3
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -29.5140 58.607 -0.504 0.620 -151.766 92.738
C(dose)[T.1] 66.4164 12.359 5.374 0.000 40.637 92.196
expression 12.6017 8.778 1.436 0.167 -5.710 30.913
Omnibus: 0.042 Durbin-Watson: 1.687
Prob(Omnibus): 0.979 Jarque-Bera (JB): 0.232
Skew: 0.072 Prob(JB): 0.890
Kurtosis: 2.529 Cond. No. 90.4

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: 04:27:49 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: 0.222
Model: OLS Adj. R-squared: 0.185
Method: Least Squares F-statistic: 6.006
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0231
Time: 04:27:49 Log-Likelihood: -110.21
No. Observations: 23 AIC: 224.4
Df Residuals: 21 BIC: 226.7
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 216.0485 55.990 3.859 0.001 99.611 332.486
expression -22.1773 9.049 -2.451 0.023 -40.996 -3.359
Omnibus: 5.246 Durbin-Watson: 2.236
Prob(Omnibus): 0.073 Jarque-Bera (JB): 2.341
Skew: 0.480 Prob(JB): 0.310
Kurtosis: 1.766 Cond. No. 55.8

CP101

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

F-statistic p-value df difference
0.084 0.778 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.554
Model: OLS Adj. R-squared: 0.433
Method: Least Squares F-statistic: 4.563
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0261
Time: 04:27:49 Log-Likelihood: -69.236
No. Observations: 15 AIC: 146.5
Df Residuals: 11 BIC: 149.3
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 224.3763 164.184 1.367 0.199 -136.990 585.743
C(dose)[T.1] -556.1413 381.962 -1.456 0.173 -1396.833 284.550
expression -24.3470 25.414 -0.958 0.359 -80.284 31.590
expression:C(dose)[T.1] 93.8759 59.188 1.586 0.141 -36.397 224.149
Omnibus: 5.838 Durbin-Watson: 0.848
Prob(Omnibus): 0.054 Jarque-Bera (JB): 3.164
Skew: -1.080 Prob(JB): 0.206
Kurtosis: 3.629 Cond. No. 405.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.453
Model: OLS Adj. R-squared: 0.361
Method: Least Squares F-statistic: 4.961
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0269
Time: 04:27:49 Log-Likelihood: -70.781
No. Observations: 15 AIC: 147.6
Df Residuals: 12 BIC: 149.7
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 112.8053 157.440 0.716 0.487 -230.228 455.838
C(dose)[T.1] 49.2154 15.685 3.138 0.009 15.040 83.391
expression -7.0392 24.359 -0.289 0.778 -60.112 46.034
Omnibus: 2.632 Durbin-Watson: 0.806
Prob(Omnibus): 0.268 Jarque-Bera (JB): 1.806
Skew: -0.829 Prob(JB): 0.405
Kurtosis: 2.622 Cond. No. 133.

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: 04:27:49 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: 0.003
Model: OLS Adj. R-squared: -0.073
Method: Least Squares F-statistic: 0.04528
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.835
Time: 04:27:49 Log-Likelihood: -75.274
No. Observations: 15 AIC: 154.5
Df Residuals: 13 BIC: 156.0
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 136.9888 203.845 0.672 0.513 -303.391 577.369
expression -6.7190 31.576 -0.213 0.835 -74.934 61.496
Omnibus: 0.654 Durbin-Watson: 1.626
Prob(Omnibus): 0.721 Jarque-Bera (JB): 0.612
Skew: 0.119 Prob(JB): 0.737
Kurtosis: 2.040 Cond. No. 133.