ECS 289A Presentation Jimin Ding. Problem & Motivation Two-component Model Estimation for Parameters in above model Define low and high level gene expression Comparing expression levels Limitations of the model and method Other possible solutions References.
David Rocke & Blythe Durbin
Journal of Computational Biology Nov.2001
--- So hypothesis testing for the difference between control and treatment need equal variance (not depending on the mean of the data);
--- So linear regression fails and log transformation has been tried;
--- So log transformation fails by inflating the variance of observations near background, and two component model is introduced.
Most of the variance is due to the additive error component. 95% CI:
Most of the variance is due to the multiplicative error component. 95% CI:
Less effective when gene is expressed at a low level in one condition and high in the other:
Background: High-level RSD:
Control and treatment)