Finding quantitative trait loci genes with collaborative targeted maximum likelihood learning

Hui Wang, Division of Biostatistics, UC Berkeley
Sherri Rose, Division of Biostatistics, University of California, Berkeley
Mark J. van der Laan, Division of Biostatistics, University of California, Berkeley

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.