LID SPN TRAP

1434243_s_at

Tomm70a translocase of outer mitochondrial membrane 70 homolog A (yeast)

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
1.489 0.237 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.680
Model: OLS Adj. R-squared: 0.630
Method: Least Squares F-statistic: 13.47
Date: Thu, 21 Nov 2024 Prob (F-statistic): 6.03e-05
Time: 04:08:18 Log-Likelihood: -99.995
No. Observations: 23 AIC: 208.0
Df Residuals: 19 BIC: 212.5
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -349.7386 300.758 -1.163 0.259 -979.232 279.755
C(dose)[T.1] 368.3880 517.600 0.712 0.485 -714.961 1451.737
expression 44.1748 32.884 1.343 0.195 -24.652 113.001
expression:C(dose)[T.1] -34.9025 54.877 -0.636 0.532 -149.762 79.957
Omnibus: 0.034 Durbin-Watson: 1.840
Prob(Omnibus): 0.983 Jarque-Bera (JB): 0.223
Skew: 0.064 Prob(JB): 0.894
Kurtosis: 2.535 Cond. No. 1.40e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.673
Model: OLS Adj. R-squared: 0.641
Method: Least Squares F-statistic: 20.62
Date: Thu, 21 Nov 2024 Prob (F-statistic): 1.38e-05
Time: 04:08:18 Log-Likelihood: -100.24
No. Observations: 23 AIC: 206.5
Df Residuals: 20 BIC: 209.9
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -235.1388 237.196 -0.991 0.333 -729.920 259.643
C(dose)[T.1] 39.3190 14.267 2.756 0.012 9.558 69.080
expression 31.6424 25.931 1.220 0.237 -22.449 85.734
Omnibus: 0.083 Durbin-Watson: 2.035
Prob(Omnibus): 0.959 Jarque-Bera (JB): 0.258
Skew: 0.112 Prob(JB): 0.879
Kurtosis: 2.532 Cond. No. 533.

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: 04:08:18 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: 0.549
Model: OLS Adj. R-squared: 0.528
Method: Least Squares F-statistic: 25.60
Date: Thu, 21 Nov 2024 Prob (F-statistic): 5.21e-05
Time: 04:08:18 Log-Likelihood: -103.94
No. Observations: 23 AIC: 211.9
Df Residuals: 21 BIC: 214.1
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -754.7128 164.996 -4.574 0.000 -1097.841 -411.585
expression 89.1851 17.627 5.059 0.000 52.527 125.843
Omnibus: 0.267 Durbin-Watson: 2.175
Prob(Omnibus): 0.875 Jarque-Bera (JB): 0.382
Skew: 0.216 Prob(JB): 0.826
Kurtosis: 2.539 Cond. No. 322.

CP101

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

F-statistic p-value df difference
0.009 0.926 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.449
Model: OLS Adj. R-squared: 0.299
Method: Least Squares F-statistic: 2.991
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0774
Time: 04:08:18 Log-Likelihood: -70.826
No. Observations: 15 AIC: 149.7
Df Residuals: 11 BIC: 152.5
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 94.2539 264.284 0.357 0.728 -487.432 675.940
C(dose)[T.1] 19.4601 656.684 0.030 0.977 -1425.891 1464.811
expression -3.0716 30.231 -0.102 0.921 -69.609 63.466
expression:C(dose)[T.1] 3.4022 74.645 0.046 0.964 -160.891 167.695
Omnibus: 2.752 Durbin-Watson: 0.820
Prob(Omnibus): 0.253 Jarque-Bera (JB): 1.891
Skew: -0.849 Prob(JB): 0.389
Kurtosis: 2.626 Cond. No. 841.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.449
Model: OLS Adj. R-squared: 0.357
Method: Least Squares F-statistic: 4.893
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0279
Time: 04:08:18 Log-Likelihood: -70.827
No. Observations: 15 AIC: 147.7
Df Residuals: 12 BIC: 149.8
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 89.3806 231.422 0.386 0.706 -414.845 593.606
C(dose)[T.1] 49.3809 15.853 3.115 0.009 14.840 83.922
expression -2.5136 26.466 -0.095 0.926 -60.179 55.151
Omnibus: 2.902 Durbin-Watson: 0.815
Prob(Omnibus): 0.234 Jarque-Bera (JB): 1.948
Skew: -0.868 Prob(JB): 0.378
Kurtosis: 2.681 Cond. No. 263.

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: 04:08:18 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: 0.004
Model: OLS Adj. R-squared: -0.073
Method: Least Squares F-statistic: 0.04999
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.827
Time: 04:08:18 Log-Likelihood: -75.271
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 27.0994 297.893 0.091 0.929 -616.460 670.659
expression 7.5883 33.938 0.224 0.827 -65.731 80.908
Omnibus: 0.659 Durbin-Watson: 1.624
Prob(Omnibus): 0.719 Jarque-Bera (JB): 0.603
Skew: 0.060 Prob(JB): 0.740
Kurtosis: 2.025 Cond. No. 261.