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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.

SUBMITTER: Wang H 

PROVIDER: S-EPMC3090625 | biostudies-literature | 2011 Jul

REPOSITORIES: biostudies-literature

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Finding Quantitative Trait Loci Genes with Collaborative Targeted Maximum Likelihood Learning.

Wang Hui H   Rose Sherri S   van der Laan Mark J MJ  

Statistics & probability letters 20110701 7


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. ...[more]

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