LID SPN TRAP

1455304_at

Unc13c unc-13 homolog C (C. elegans)

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
0.434 0.517 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.685
Model: OLS Adj. R-squared: 0.635
Method: Least Squares F-statistic: 13.78
Date: Thu, 21 Nov 2024 Prob (F-statistic): 5.21e-05
Time: 05:00:25 Log-Likelihood: -99.814
No. Observations: 23 AIC: 207.6
Df Residuals: 19 BIC: 212.2
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -255.2313 210.646 -1.212 0.240 -696.119 185.656
C(dose)[T.1] 381.9191 250.162 1.527 0.143 -141.676 905.514
expression 34.5786 23.530 1.470 0.158 -14.669 83.827
expression:C(dose)[T.1] -36.7113 27.914 -1.315 0.204 -95.136 21.713
Omnibus: 0.094 Durbin-Watson: 1.389
Prob(Omnibus): 0.954 Jarque-Bera (JB): 0.312
Skew: -0.063 Prob(JB): 0.856
Kurtosis: 2.444 Cond. No. 760.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.657
Model: OLS Adj. R-squared: 0.622
Method: Least Squares F-statistic: 19.11
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.29e-05
Time: 05:00:25 Log-Likelihood: -100.82
No. Observations: 23 AIC: 207.6
Df Residuals: 20 BIC: 211.0
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -21.8018 115.490 -0.189 0.852 -262.711 219.107
C(dose)[T.1] 53.1079 8.683 6.116 0.000 34.995 71.221
expression 8.4938 12.888 0.659 0.517 -18.390 35.378
Omnibus: 0.519 Durbin-Watson: 1.774
Prob(Omnibus): 0.771 Jarque-Bera (JB): 0.627
Skew: 0.228 Prob(JB): 0.731
Kurtosis: 2.332 Cond. No. 242.

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: 05:00:25 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: 0.014
Model: OLS Adj. R-squared: -0.033
Method: Least Squares F-statistic: 0.2994
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.590
Time: 05:00:25 Log-Likelihood: -112.94
No. Observations: 23 AIC: 229.9
Df Residuals: 21 BIC: 232.2
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -24.6992 190.950 -0.129 0.898 -421.802 372.403
expression 11.6513 21.292 0.547 0.590 -32.628 55.931
Omnibus: 2.264 Durbin-Watson: 2.530
Prob(Omnibus): 0.322 Jarque-Bera (JB): 1.559
Skew: 0.423 Prob(JB): 0.459
Kurtosis: 2.045 Cond. No. 242.

CP101

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

F-statistic p-value df difference
1.836 0.200 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.523
Model: OLS Adj. R-squared: 0.392
Method: Least Squares F-statistic: 4.014
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0373
Time: 05:00:25 Log-Likelihood: -69.754
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 220.1809 124.483 1.769 0.105 -53.805 494.167
C(dose)[T.1] 5.2276 282.568 0.019 0.986 -616.699 627.155
expression -16.0510 13.028 -1.232 0.244 -44.725 12.623
expression:C(dose)[T.1] 3.9878 30.978 0.129 0.900 -64.195 72.171
Omnibus: 2.803 Durbin-Watson: 0.870
Prob(Omnibus): 0.246 Jarque-Bera (JB): 1.743
Skew: -0.829 Prob(JB): 0.418
Kurtosis: 2.808 Cond. No. 407.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.522
Model: OLS Adj. R-squared: 0.442
Method: Least Squares F-statistic: 6.550
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0119
Time: 05:00:25 Log-Likelihood: -69.765
No. Observations: 15 AIC: 145.5
Df Residuals: 12 BIC: 147.7
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 213.4691 108.307 1.971 0.072 -22.512 449.450
C(dose)[T.1] 41.5411 15.709 2.644 0.021 7.314 75.768
expression -15.3457 11.325 -1.355 0.200 -40.021 9.329
Omnibus: 2.919 Durbin-Watson: 0.837
Prob(Omnibus): 0.232 Jarque-Bera (JB): 1.815
Skew: -0.847 Prob(JB): 0.404
Kurtosis: 2.819 Cond. No. 139.

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: 05:00:25 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: 0.243
Model: OLS Adj. R-squared: 0.185
Method: Least Squares F-statistic: 4.181
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0617
Time: 05:00:25 Log-Likelihood: -73.209
No. Observations: 15 AIC: 150.4
Df Residuals: 13 BIC: 151.8
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 335.2559 118.487 2.829 0.014 79.280 591.231
expression -26.1159 12.773 -2.045 0.062 -53.710 1.478
Omnibus: 5.298 Durbin-Watson: 1.883
Prob(Omnibus): 0.071 Jarque-Bera (JB): 1.539
Skew: 0.238 Prob(JB): 0.463
Kurtosis: 1.505 Cond. No. 126.