LID SPN TRAP

1458539_at

R3hdm1 R3H domain 1 (binds single-stranded nucleic acids)

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
5.830 0.025 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.729
Model: OLS Adj. R-squared: 0.686
Method: Least Squares F-statistic: 17.00
Date: Thu, 21 Nov 2024 Prob (F-statistic): 1.31e-05
Time: 04:05:04 Log-Likelihood: -98.109
No. Observations: 23 AIC: 204.2
Df Residuals: 19 BIC: 208.8
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 1461.8779 1121.024 1.304 0.208 -884.453 3808.209
C(dose)[T.1] 255.8493 1380.938 0.185 0.855 -2634.488 3146.187
expression -120.9472 96.317 -1.256 0.224 -322.542 80.648
expression:C(dose)[T.1] -16.5831 118.410 -0.140 0.890 -264.418 231.252
Omnibus: 2.569 Durbin-Watson: 2.112
Prob(Omnibus): 0.277 Jarque-Bera (JB): 1.219
Skew: -0.100 Prob(JB): 0.544
Kurtosis: 1.890 Cond. No. 5.73e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.728
Model: OLS Adj. R-squared: 0.701
Method: Least Squares F-statistic: 26.80
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.19e-06
Time: 04:05:04 Log-Likelihood: -98.121
No. Observations: 23 AIC: 202.2
Df Residuals: 20 BIC: 205.6
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 1589.5811 635.902 2.500 0.021 263.113 2916.049
C(dose)[T.1] 62.4560 8.591 7.270 0.000 44.534 80.378
expression -131.9195 54.635 -2.415 0.025 -245.886 -17.953
Omnibus: 2.878 Durbin-Watson: 2.158
Prob(Omnibus): 0.237 Jarque-Bera (JB): 1.283
Skew: -0.100 Prob(JB): 0.527
Kurtosis: 1.860 Cond. No. 1.94e+03

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: 04:05:04 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: 0.010
Model: OLS Adj. R-squared: -0.037
Method: Least Squares F-statistic: 0.2179
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.645
Time: 04:05:04 Log-Likelihood: -112.99
No. Observations: 23 AIC: 230.0
Df Residuals: 21 BIC: 232.2
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -418.2840 1066.805 -0.392 0.699 -2636.826 1800.258
expression 42.6672 91.398 0.467 0.645 -147.406 232.740
Omnibus: 2.970 Durbin-Watson: 2.421
Prob(Omnibus): 0.227 Jarque-Bera (JB): 1.590
Skew: 0.342 Prob(JB): 0.452
Kurtosis: 1.909 Cond. No. 1.75e+03

CP101

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

F-statistic p-value df difference
0.520 0.485 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.476
Model: OLS Adj. R-squared: 0.333
Method: Least Squares F-statistic: 3.330
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0601
Time: 04:05:04 Log-Likelihood: -70.454
No. Observations: 15 AIC: 148.9
Df Residuals: 11 BIC: 151.7
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -255.9766 1434.988 -0.178 0.862 -3414.363 2902.410
C(dose)[T.1] -516.9550 1892.346 -0.273 0.790 -4681.981 3648.071
expression 28.3647 125.854 0.225 0.826 -248.637 305.367
expression:C(dose)[T.1] 50.0240 166.299 0.301 0.769 -315.998 416.046
Omnibus: 2.535 Durbin-Watson: 0.714
Prob(Omnibus): 0.282 Jarque-Bera (JB): 1.667
Skew: -0.615 Prob(JB): 0.434
Kurtosis: 1.924 Cond. No. 3.72e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.472
Model: OLS Adj. R-squared: 0.384
Method: Least Squares F-statistic: 5.356
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0218
Time: 04:05:04 Log-Likelihood: -70.515
No. Observations: 15 AIC: 147.0
Df Residuals: 12 BIC: 149.2
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -582.6383 901.783 -0.646 0.530 -2547.455 1382.178
C(dose)[T.1] 52.2548 15.983 3.269 0.007 17.431 87.078
expression 57.0151 79.086 0.721 0.485 -115.299 229.329
Omnibus: 2.404 Durbin-Watson: 0.669
Prob(Omnibus): 0.301 Jarque-Bera (JB): 1.554
Skew: -0.570 Prob(JB): 0.460
Kurtosis: 1.911 Cond. No. 1.35e+03

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: 04:05:04 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: 0.001
Model: OLS Adj. R-squared: -0.076
Method: Least Squares F-statistic: 0.01330
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.910
Time: 04:05:04 Log-Likelihood: -75.292
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 225.7878 1145.693 0.197 0.847 -2249.331 2700.906
expression -11.6170 100.734 -0.115 0.910 -229.239 206.005
Omnibus: 0.421 Durbin-Watson: 1.634
Prob(Omnibus): 0.810 Jarque-Bera (JB): 0.507
Skew: 0.016 Prob(JB): 0.776
Kurtosis: 2.100 Cond. No. 1.29e+03