LID SPN TRAP

1459867_x_at

Unc45a unc-45 homolog A (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
0.069 0.795 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.671
Model: OLS Adj. R-squared: 0.619
Method: Least Squares F-statistic: 12.93
Date: Thu, 21 Nov 2024 Prob (F-statistic): 7.81e-05
Time: 03:32:17 Log-Likelihood: -100.31
No. Observations: 23 AIC: 208.6
Df Residuals: 19 BIC: 213.2
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -19.6852 148.189 -0.133 0.896 -329.848 290.478
C(dose)[T.1] 311.3439 234.451 1.328 0.200 -179.368 802.056
expression 15.4241 30.907 0.499 0.623 -49.264 80.112
expression:C(dose)[T.1] -53.1335 48.355 -1.099 0.286 -154.342 48.075
Omnibus: 0.104 Durbin-Watson: 1.625
Prob(Omnibus): 0.949 Jarque-Bera (JB): 0.267
Skew: 0.131 Prob(JB): 0.875
Kurtosis: 2.541 Cond. No. 339.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.650
Model: OLS Adj. R-squared: 0.615
Method: Least Squares F-statistic: 18.59
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.74e-05
Time: 03:32:17 Log-Likelihood: -101.02
No. Observations: 23 AIC: 208.0
Df Residuals: 20 BIC: 211.5
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 84.3051 114.623 0.735 0.471 -154.794 323.404
C(dose)[T.1] 53.9129 9.024 5.974 0.000 35.088 72.738
expression -6.2822 23.892 -0.263 0.795 -56.121 43.556
Omnibus: 0.543 Durbin-Watson: 1.901
Prob(Omnibus): 0.762 Jarque-Bera (JB): 0.605
Skew: 0.089 Prob(JB): 0.739
Kurtosis: 2.225 Cond. No. 133.

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: 03:32:17 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: 0.026
Model: OLS Adj. R-squared: -0.020
Method: Least Squares F-statistic: 0.5643
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.461
Time: 03:32:17 Log-Likelihood: -112.80
No. Observations: 23 AIC: 229.6
Df Residuals: 21 BIC: 231.9
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -57.3676 182.621 -0.314 0.757 -437.148 322.413
expression 28.3549 37.745 0.751 0.461 -50.140 106.850
Omnibus: 3.050 Durbin-Watson: 2.323
Prob(Omnibus): 0.218 Jarque-Bera (JB): 1.623
Skew: 0.350 Prob(JB): 0.444
Kurtosis: 1.904 Cond. No. 129.

CP101

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

F-statistic p-value df difference
2.779 0.121 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.612
Model: OLS Adj. R-squared: 0.506
Method: Least Squares F-statistic: 5.786
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0126
Time: 03:32:17 Log-Likelihood: -68.198
No. Observations: 15 AIC: 144.4
Df Residuals: 11 BIC: 147.2
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 87.7473 107.788 0.814 0.433 -149.493 324.988
C(dose)[T.1] 257.5072 151.928 1.695 0.118 -76.885 591.899
expression -4.0268 21.268 -0.189 0.853 -50.838 42.785
expression:C(dose)[T.1] -37.3683 28.727 -1.301 0.220 -100.596 25.860
Omnibus: 1.483 Durbin-Watson: 1.139
Prob(Omnibus): 0.476 Jarque-Bera (JB): 0.951
Skew: -0.596 Prob(JB): 0.622
Kurtosis: 2.680 Cond. No. 165.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.552
Model: OLS Adj. R-squared: 0.478
Method: Least Squares F-statistic: 7.405
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00804
Time: 03:32:17 Log-Likelihood: -69.271
No. Observations: 15 AIC: 144.5
Df Residuals: 12 BIC: 146.7
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 191.1005 74.910 2.551 0.025 27.886 354.315
C(dose)[T.1] 60.8945 15.824 3.848 0.002 26.417 95.372
expression -24.5098 14.703 -1.667 0.121 -56.546 7.526
Omnibus: 1.491 Durbin-Watson: 1.274
Prob(Omnibus): 0.475 Jarque-Bera (JB): 1.177
Skew: -0.515 Prob(JB): 0.555
Kurtosis: 2.094 Cond. No. 58.9

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: 03:32:17 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: 0.000
Model: OLS Adj. R-squared: -0.077
Method: Least Squares F-statistic: 0.0009482
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.976
Time: 03:32:17 Log-Likelihood: -75.300
No. Observations: 15 AIC: 154.6
Df Residuals: 13 BIC: 156.0
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 90.5779 100.821 0.898 0.385 -127.233 308.388
expression 0.5827 18.925 0.031 0.976 -40.302 41.467
Omnibus: 0.614 Durbin-Watson: 1.608
Prob(Omnibus): 0.736 Jarque-Bera (JB): 0.585
Skew: 0.043 Prob(JB): 0.747
Kurtosis: 2.037 Cond. No. 54.7