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使用惩罚似然估计模糊基因型的单体型。

Haplotype estimation from fuzzy genotypes using penalized likelihood.

机构信息

Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands.

出版信息

PLoS One. 2011;6(9):e24219. doi: 10.1371/journal.pone.0024219. Epub 2011 Sep 8.

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.

摘要

复合链接模型是广义线性模型的推广,其中观测计数的期望值被构建为广义线性分量的和。当与惩罚似然结合使用时,它提供了一种从观测基因型估计单倍型概率的强大而优雅的方法。不确定(“模糊”)的基因型,如 AFLP 分数产生的基因型,可以通过向模型添加额外的层来处理。我们描述了模型和估计算法。我们将其应用于准确的人类单核苷酸多态性 (SNP)数据集和模糊番茄 AFLP 分数数据集。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57cf/3169573/efd38a7da33d/pone.0024219.g001.jpg

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