haplotype estimation from fuzzy genotypes using penalized likelihood单体型使用惩罚似然估计从模糊基因型.pdfVIP

Haplotype Estimation from Fuzzy Genotypes Using Penalized Likelihood 1 2,3 Hae-Won Uh *, Paul H. C. Eilers 1 Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands, 2 Erasmus Medical Center, Rotterdam, The Netherlands, 3 Centre for Biosystems Genomics, Wageningen, The Netherlands Abstract The Composite Link Model is a generalization of the generalized linear model in which expected values of observed counts are constructed as a sum of generalized linear components. When combined with penalized likelihood, it provides a powerful and elegant way to estimate haplotype probabilities from observed genotypes. Uncertain (‘‘fuzzy’’) genotypes, like those resulting from AFLP scores, can be handled by adding an extra layer to the model. We describe the model and the estimation algorithm. We apply it to a data set of accurate human single nucleotide polymorphism (SNP) and to a data set of fuzzy tomato AFLP scores. Citation: Uh H-W, Eilers PHC (2011) Haplotype Estimation from Fuzzy Genotypes Using Penalized Likelihood. PLoS ONE 6(9): e24219. doi:10.1371/ journal.pone.0024219 Editor: Thomas Mailund, Aarhus University, Denmark Received December 29, 2010; Accepted August 8, 2011; Published September 8, 2011 Copyright: 2011 Uh and Eilers. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This project was co-financed by the Centre for BioSystems Genomics (CBSG), which is part of the Netherlands Genomics Initiative / Netherlands Organisation for Scientific Research. The funders had no role in study design, data collection and analysis, dec