LID SPN TRAP

1423845_at

Csdc2 cold shock domain containing C2, RNA binding

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
0.421 0.524 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.672
Model: OLS Adj. R-squared: 0.620
Method: Least Squares F-statistic: 12.98
Date: Thu, 21 Nov 2024 Prob (F-statistic): 7.61e-05
Time: 03:33:00 Log-Likelihood: -100.28
No. Observations: 23 AIC: 208.6
Df Residuals: 19 BIC: 213.1
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 47.5624 150.347 0.316 0.755 -267.117 362.241
C(dose)[T.1] 302.5509 258.562 1.170 0.256 -238.626 843.728
expression 0.6957 15.726 0.044 0.965 -32.220 33.611
expression:C(dose)[T.1] -25.3752 26.551 -0.956 0.351 -80.947 30.197
Omnibus: 1.466 Durbin-Watson: 1.829
Prob(Omnibus): 0.480 Jarque-Bera (JB): 0.958
Skew: 0.127 Prob(JB): 0.619
Kurtosis: 2.033 Cond. No. 710.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.656
Model: OLS Adj. R-squared: 0.622
Method: Least Squares F-statistic: 19.09
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.30e-05
Time: 03:33:00 Log-Likelihood: -100.82
No. Observations: 23 AIC: 207.6
Df Residuals: 20 BIC: 211.1
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 132.6001 120.927 1.097 0.286 -119.649 384.849
C(dose)[T.1] 55.6029 9.355 5.944 0.000 36.089 75.116
expression -8.2063 12.643 -0.649 0.524 -34.580 18.167
Omnibus: 0.533 Durbin-Watson: 1.827
Prob(Omnibus): 0.766 Jarque-Bera (JB): 0.594
Skew: 0.044 Prob(JB): 0.743
Kurtosis: 2.218 Cond. No. 274.

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: 03:33:00 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: 0.049
Model: OLS Adj. R-squared: 0.004
Method: Least Squares F-statistic: 1.085
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.309
Time: 03:33:00 Log-Likelihood: -112.53
No. Observations: 23 AIC: 229.1
Df Residuals: 21 BIC: 231.3
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -112.4019 184.532 -0.609 0.549 -496.158 271.354
expression 19.8374 19.040 1.042 0.309 -19.759 59.434
Omnibus: 3.085 Durbin-Watson: 2.633
Prob(Omnibus): 0.214 Jarque-Bera (JB): 1.599
Skew: 0.333 Prob(JB): 0.450
Kurtosis: 1.894 Cond. No. 257.

CP101

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

F-statistic p-value df difference
2.847 0.117 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.568
Model: OLS Adj. R-squared: 0.450
Method: Least Squares F-statistic: 4.818
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0222
Time: 03:33:00 Log-Likelihood: -69.008
No. Observations: 15 AIC: 146.0
Df Residuals: 11 BIC: 148.8
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -440.0006 492.120 -0.894 0.390 -1523.150 643.148
C(dose)[T.1] 362.2383 511.358 0.708 0.493 -763.254 1487.730
expression 54.6740 53.012 1.031 0.325 -62.005 171.353
expression:C(dose)[T.1] -32.3194 55.356 -0.584 0.571 -154.157 89.518
Omnibus: 2.183 Durbin-Watson: 1.303
Prob(Omnibus): 0.336 Jarque-Bera (JB): 0.631
Skew: -0.435 Prob(JB): 0.729
Kurtosis: 3.504 Cond. No. 1.01e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.554
Model: OLS Adj. R-squared: 0.480
Method: Least Squares F-statistic: 7.467
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00782
Time: 03:33:00 Log-Likelihood: -69.237
No. Observations: 15 AIC: 144.5
Df Residuals: 12 BIC: 146.6
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -164.9078 138.095 -1.194 0.255 -465.790 135.975
C(dose)[T.1] 63.8498 16.603 3.846 0.002 27.674 100.025
expression 25.0335 14.838 1.687 0.117 -7.295 57.362
Omnibus: 2.460 Durbin-Watson: 1.246
Prob(Omnibus): 0.292 Jarque-Bera (JB): 0.744
Skew: -0.455 Prob(JB): 0.690
Kurtosis: 3.602 Cond. No. 179.

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: 03:33:00 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: 0.005
Model: OLS Adj. R-squared: -0.071
Method: Least Squares F-statistic: 0.07033
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.795
Time: 03:33:00 Log-Likelihood: -75.260
No. Observations: 15 AIC: 154.5
Df Residuals: 13 BIC: 155.9
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 136.8442 163.125 0.839 0.417 -215.565 489.254
expression -4.8142 18.153 -0.265 0.795 -44.031 34.403
Omnibus: 0.688 Durbin-Watson: 1.547
Prob(Omnibus): 0.709 Jarque-Bera (JB): 0.611
Skew: 0.047 Prob(JB): 0.737
Kurtosis: 2.015 Cond. No. 146.