| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1152574 | Statistics & Probability Letters | 2011 | 5 Pages |
Abstract
Quantitative trait loci mapping is focused on identifying the positions and effect of genes underlying an observed trait. We present a collaborative targeted maximum likelihood estimator in a semi-parametric model using a newly proposed 2-part super learning algorithm to find quantitative trait loci genes in listeria data. Results are compared to the parametric composite interval mapping approach.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Hui Wang, Sherri Rose, Mark J. van der Laan,