LID SPN TRAP

1451147_x_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
0.281 0.602 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.664
Model: OLS Adj. R-squared: 0.611
Method: Least Squares F-statistic: 12.54
Date: Thu, 21 Nov 2024 Prob (F-statistic): 9.43e-05
Time: 04:18:28 Log-Likelihood: -100.55
No. Observations: 23 AIC: 209.1
Df Residuals: 19 BIC: 213.6
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 45.3283 173.400 0.261 0.797 -317.601 408.258
C(dose)[T.1] 279.3164 290.826 0.960 0.349 -329.389 888.022
expression 0.9375 18.296 0.051 0.960 -37.357 39.232
expression:C(dose)[T.1] -23.1761 30.105 -0.770 0.451 -86.187 39.835
Omnibus: 1.258 Durbin-Watson: 1.837
Prob(Omnibus): 0.533 Jarque-Bera (JB): 0.881
Skew: 0.099 Prob(JB): 0.644
Kurtosis: 2.062 Cond. No. 789.

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.654
Model: OLS Adj. R-squared: 0.619
Method: Least Squares F-statistic: 18.89
Date: Thu, 21 Nov 2024 Prob (F-statistic): 2.46e-05
Time: 04:18:28 Log-Likelihood: -100.90
No. Observations: 23 AIC: 207.8
Df Residuals: 20 BIC: 211.2
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept 126.4056 136.343 0.927 0.365 -158.000 410.811
C(dose)[T.1] 55.5528 9.660 5.751 0.000 35.402 75.703
expression -7.6225 14.381 -0.530 0.602 -37.620 22.375
Omnibus: 0.478 Durbin-Watson: 1.818
Prob(Omnibus): 0.787 Jarque-Bera (JB): 0.567
Skew: 0.042 Prob(JB): 0.753
Kurtosis: 2.235 Cond. No. 305.

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: 04:18:28 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: 0.082
Model: OLS Adj. R-squared: 0.038
Method: Least Squares F-statistic: 1.867
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.186
Time: 04:18:28 Log-Likelihood: -112.13
No. Observations: 23 AIC: 228.3
Df Residuals: 21 BIC: 230.5
Df Model: 1
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -190.9500 198.198 -0.963 0.346 -603.124 221.224
expression 28.1634 20.610 1.366 0.186 -14.698 71.025
Omnibus: 2.672 Durbin-Watson: 2.686
Prob(Omnibus): 0.263 Jarque-Bera (JB): 1.489
Skew: 0.324 Prob(JB): 0.475
Kurtosis: 1.935 Cond. No. 279.

CP101

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

F-statistic p-value df difference
2.467 0.142 1.0

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

OLS Regression Results
Dep. Variable: AIM R-squared: 0.547
Model: OLS Adj. R-squared: 0.424
Method: Least Squares F-statistic: 4.434
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.0283
Time: 04:18:28 Log-Likelihood: -69.355
No. Observations: 15 AIC: 146.7
Df Residuals: 11 BIC: 149.5
Df Model: 3
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -342.5777 514.242 -0.666 0.519 -1474.418 789.262
C(dose)[T.1] 241.4015 539.916 0.447 0.663 -946.946 1429.749
expression 44.8029 56.181 0.797 0.442 -78.850 168.456
expression:C(dose)[T.1] -19.7419 59.272 -0.333 0.745 -150.199 110.716
Omnibus: 2.484 Durbin-Watson: 1.258
Prob(Omnibus): 0.289 Jarque-Bera (JB): 0.820
Skew: -0.512 Prob(JB): 0.664
Kurtosis: 3.512 Cond. No. 1.03e+03

Model:
AIM ~ expression + C(dose)

OLS Regression Results
Dep. Variable: AIM R-squared: 0.543
Model: OLS Adj. R-squared: 0.467
Method: Least Squares F-statistic: 7.123
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.00914
Time: 04:18:29 Log-Likelihood: -69.431
No. Observations: 15 AIC: 144.9
Df Residuals: 12 BIC: 147.0
Df Model: 2
coef std err t P>|t| [95.0% Conf. Int.]
Intercept -180.2693 158.038 -1.141 0.276 -524.605 164.066
C(dose)[T.1] 61.6609 16.385 3.763 0.003 25.962 97.360
expression 27.0669 17.231 1.571 0.142 -10.477 64.611
Omnibus: 2.666 Durbin-Watson: 1.237
Prob(Omnibus): 0.264 Jarque-Bera (JB): 0.877
Skew: -0.510 Prob(JB): 0.645
Kurtosis: 3.601 Cond. No. 200.

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: 04:18:29 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: 0.003
Model: OLS Adj. R-squared: -0.074
Method: Least Squares F-statistic: 0.04117
Date: Thu, 21 Nov 2024 Prob (F-statistic): 0.842
Time: 04:18:29 Log-Likelihood: -75.276
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 132.3152 190.737 0.694 0.500 -279.747 544.378
expression -4.3397 21.387 -0.203 0.842 -50.544 41.864
Omnibus: 0.700 Durbin-Watson: 1.561
Prob(Omnibus): 0.705 Jarque-Bera (JB): 0.616
Skew: 0.050 Prob(JB): 0.735
Kurtosis: 2.012 Cond. No. 170.