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.
PMCID: PMC3090625
Statistics and Probability Letters
2011
http://www.ncbi.nlm.nih.gov/pubmed/?term=Finding%20quantitative%20trait%20loci%20genes%20with%20collaborative%20targeted%20maximum%20likelihood%20learning