title: Finding Quantitative Trait Loci Genes with Collaborative Targeted Maximum Likelihood Learning.
abstract: Quantitative trait loci mapping is focused on identifying the positions and effect of genes underlying an 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.
authors.affiliation: University of California, Berkeley, School of Public Health, Division of Biostatistics, 101 Haviland Hall, #7358, Berkeley, CA 94720, USA.
authors.forename: Hui
authors.initials: H
authors.lastname: Wang
authors.forename: Sherri
authors.initials: S
authors.lastname: Rose
authors.forename: Mark J
authors.initials: MJ
authors.lastname: van der Laan