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Finding quantitative trait loci genes with collaborative targeted maximum likelihood learning

Listed author(s):
  • Wang, Hui
  • Rose, Sherri
  • van der Laan, Mark J.
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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.

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Article provided by Elsevier in its journal Statistics & Probability Letters.

Volume (Year): 81 (2011)
Issue (Month): 7 (July)
Pages: 792-796

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Handle: RePEc:eee:stapro:v:81:y:2011:i:7:p:792-796
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  1. Sinisi Sandra E & van der Laan Mark J., 2004. "Deletion/Substitution/Addition Algorithm in Learning with Applications in Genomics," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 3(1), pages 1-40, August.
  2. van der Laan Mark J. & Polley Eric C & Hubbard Alan E., 2007. "Super Learner," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 6(1), pages 1-23, September.
  3. van der Laan Mark J. & Rubin Daniel, 2006. "Targeted Maximum Likelihood Learning," The International Journal of Biostatistics, De Gruyter, vol. 2(1), pages 1-40, December.
  4. Jin, Chunfang & Fine, Jason P. & Yandell, Brian S., 2007. "A Unified Semiparametric Framework for Quantitative Trait Loci Analyses, With Application to Spike Phenotypes," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 56-67, March.
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