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Permanent link (DOI): https://doi.org/10.7939/R3BV7B83D

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Whole genome SNP genotype piecemeal imputation Open Access

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Author or creator
Wang, Yining
Wylie, Tim
Stothard, Paul
Lin, Guohui
Additional contributors
Subject/Keyword
Sequence
Inferring Missing Genotypes
Phase
Cattle
Haplotype Inference
Information
Wide Association
Population-Data
Type of item
Journal Article (Published)
Language
English
Place
Time
Description
Background Despite ongoing reductions in the cost of sequencing technologies, whole genome SNP genotype imputation is often used as an alternative for obtaining abundant SNP genotypes for genome wide association studies. Several existing genotype imputation methods can be efficient for this purpose, while achieving various levels of imputation accuracy. Recent empirical results have shown that the two-step imputation may improve accuracy by imputing the low density genotyped study animals to a medium density array first and then to the target density. We are interested in building a series of staircase arrays that lead the low density array to the high density array or even the whole genome, such that genotype imputation along these staircases can achieve the highest accuracy. Results For genotype imputation from a lower density to a higher density, we first show how to select untyped SNPs to construct a medium density array. Subsequently, we determine for each selected SNP those untyped SNPs to be imputed in the add-one two-step imputation, and lastly how the clusters of imputed genotype are pieced together as the final imputation result. We design extensive empirical experiments using several hundred sequenced and genotyped animals to demonstrate that our novel two-step piecemeal imputation always achieves an improvement compared to the one-step imputation by the state-of-the-art methods Beagle and FImpute. Using the two-step piecemeal imputation, we present some preliminary success on whole genome SNP genotype imputation for genotyped animals via a series of staircase arrays. Conclusions From a low SNP density to the whole genome, intermediate pseudo-arrays can be computationally constructed by selecting the most informative SNPs for untyped SNP genotype imputation. Such pseudo-array staircases are able to impute more accurately than the classic one-step imputation.
Date created
2015
DOI
doi:10.7939/R3BV7B83D
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Attribution 4.0 International
Citation for previous publication
Wang, Y., Wylie, T., Stothard, P., & Lin, G. (2015). Whole genome SNP genotype piecemeal imputation. BMC Bioinformatics, 16(340), [11 pages].  http://dx.doi.org/10.1186/s12859-015-0770-2

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File format: pdf (Portable Document Format)
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File size: 706881
Last modified: 2017:09:06 16:06:40-06:00
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File title: Abstract
File title: Whole Genome SNP Genotype Piecemeal Imputation
File author: Yining Wang
Page count: 11
File language: EN
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