Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

    We have a manual that explains all the features 

Record number 495256
Title Reconstruction of genome ancestry blocks in multiparental populations
Author(s) Zheng, Chaozhi; Boer, M.P.; Eeuwijk, F.A. van
Source Genetics 200 (2015)4. - ISSN 0016-6731 - p. 1073 - 1087.
DOI http://dx.doi.org/10.1534/genetics.115.177873
Department(s) Biometris (WU MAT)
Biometris (PPO/PRI)
PE&RC
Publication type Refereed Article in a scientific journal
Publication year 2015
Keyword(s) Collaborative cross (CC) - Diversity outcross (DO) - Haplotype reconstruction - Hidden Markov model - MPP - Multiparent advanced generation inter-cross (MAGIC) - Multiparental populations
Abstract

We present a general hidden Markov model framework called reconstructing ancestry blocks bit by bit (RABBIT) for reconstructing genome ancestry blocks from single-nucleotide polymorphism (SNP) array data, a required step for quantitative trait locus (QTL) mapping. The framework can be applied to a wide range of mapping populations such as the Arabidopsis multiparent advanced generation intercross (MAGIC), the mouse Collaborative Cross (CC), and the diversity outcross (DO) for both autosomes and X chromosomes if they exist. The model underlying RABBIT accounts for the joint pattern of recombination breakpoints between two homologous chromosomes and missing data and allelic typing errors in the genotype data of both sampled individuals and founders. Studies on simulated data of the MAGIC and the CC and real data of the MAGIC, the DO, and the CC demonstrate that RABBIT is more robust and accurate in reconstructing recombination bin maps than some commonly used methods.

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