LID SPN TRAP

1456489_at

Pcf11 cleavage and polyadenylation factor subunit homolog (S. cerevisiae)

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
2.090 0.164 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.732
Model: OLS Adj. R-squared: 0.690
Method: Least Squares F-statistic: 17.33
Date: Mon, 27 Jan 2025 Prob (F-statistic): 1.15e-05
Time: 22:01:56 Log-Likelihood: -97.949
No. Observations: 23 AIC: 203.9
Df Residuals: 19 BIC: 208.4
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -22.7491 207.284 -0.110 0.914 -456.599 411.101
C(dose)[T.1] 586.4920 281.180 2.086 0.051 -2.025 1175.009
expression 8.2010 22.082 0.371 0.714 -38.016 54.418
expression:C(dose)[T.1] -56.0365 29.734 -1.885 0.075 -118.271 6.198
Omnibus: 1.267 Durbin-Watson: 2.295
Prob(Omnibus): 0.531 Jarque-Bera (JB): 0.978
Skew: 0.483 Prob(JB): 0.613
Kurtosis: 2.701 Cond. No. 909.

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: 21.47
Date: Mon, 27 Jan 2025 Prob (F-statistic): 1.05e-05
Time: 22:01:56 Log-Likelihood: -99.920
No. Observations: 23 AIC: 205.8
Df Residuals: 20 BIC: 209.2
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 267.2572 147.469 1.812 0.085 -40.358 574.872
C(dose)[T.1] 56.8075 8.683 6.542 0.000 38.695 74.920
expression -22.7036 15.703 -1.446 0.164 -55.459 10.052
Omnibus: 3.561 Durbin-Watson: 2.288
Prob(Omnibus): 0.169 Jarque-Bera (JB): 1.422
Skew: 0.117 Prob(JB): 0.491
Kurtosis: 1.805 Cond. No. 339.

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: Mon, 27 Jan 2025 Prob (F-statistic): 3.51e-06
Time: 22:01:56 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: 0.002
Model: OLS Adj. R-squared: -0.045
Method: Least Squares F-statistic: 0.04764
Date: Mon, 27 Jan 2025 Prob (F-statistic): 0.829
Time: 22:01:56 Log-Likelihood: -113.08
No. Observations: 23 AIC: 230.2
Df Residuals: 21 BIC: 232.4
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 25.8473 246.912 0.105 0.918 -487.634 539.329
expression 5.6963 26.098 0.218 0.829 -48.577 59.969
Omnibus: 3.137 Durbin-Watson: 2.426
Prob(Omnibus): 0.208 Jarque-Bera (JB): 1.620
Skew: 0.339 Prob(JB): 0.445
Kurtosis: 1.890 Cond. No. 328.

CP101

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

F-statistic p-value df difference
0.160 0.696 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.457
Model: OLS Adj. R-squared: 0.309
Method: Least Squares F-statistic: 3.089
Date: Mon, 27 Jan 2025 Prob (F-statistic): 0.0719
Time: 22:01:56 Log-Likelihood: -70.717
No. Observations: 15 AIC: 149.4
Df Residuals: 11 BIC: 152.3
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -203.0181 958.191 -0.212 0.836 -2311.983 1905.947
C(dose)[T.1] 206.9683 1028.087 0.201 0.844 -2055.836 2469.773
expression 28.1561 99.749 0.282 0.783 -191.390 247.702
expression:C(dose)[T.1] -16.6054 106.806 -0.155 0.879 -251.684 218.473
Omnibus: 2.452 Durbin-Watson: 0.939
Prob(Omnibus): 0.294 Jarque-Bera (JB): 1.663
Skew: -0.795 Prob(JB): 0.435
Kurtosis: 2.636 Cond. No. 1.94e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.456
Model: OLS Adj. R-squared: 0.365
Method: Least Squares F-statistic: 5.030
Date: Mon, 27 Jan 2025 Prob (F-statistic): 0.0259
Time: 22:01:56 Log-Likelihood: -70.734
No. Observations: 15 AIC: 147.5
Df Residuals: 12 BIC: 149.6
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -63.8992 328.470 -0.195 0.849 -779.574 651.776
C(dose)[T.1] 47.1509 16.451 2.866 0.014 11.308 82.993
expression 13.6725 34.176 0.400 0.696 -60.791 88.136
Omnibus: 2.551 Durbin-Watson: 0.910
Prob(Omnibus): 0.279 Jarque-Bera (JB): 1.717
Skew: -0.811 Prob(JB): 0.424
Kurtosis: 2.655 Cond. No. 413.

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: Mon, 27 Jan 2025 Prob (F-statistic): 0.00629
Time: 22:01:56 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: 0.084
Model: OLS Adj. R-squared: 0.013
Method: Least Squares F-statistic: 1.186
Date: Mon, 27 Jan 2025 Prob (F-statistic): 0.296
Time: 22:01:56 Log-Likelihood: -74.645
No. Observations: 15 AIC: 153.3
Df Residuals: 13 BIC: 154.7
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -333.6269 392.434 -0.850 0.411 -1181.429 514.175
expression 44.1188 40.507 1.089 0.296 -43.391 131.629
Omnibus: 0.418 Durbin-Watson: 1.912
Prob(Omnibus): 0.812 Jarque-Bera (JB): 0.521
Skew: 0.160 Prob(JB): 0.771
Kurtosis: 2.145 Cond. No. 395.