Statistical and Computational Challenges in Whole Genome Prediction and Genome-Wide Association Analyses for Plant and Animal Breeding

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Statistical and Computational Challenges in Whole Genome Prediction and Genome-Wide Association Analyses for Plant and Animal Breeding

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wetenschappelijk artikel

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наукова стаття, опублікована у вересні 2015

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Statistical and Computational ...... for Plant and Animal Breeding

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Statistical and Computational ...... for Plant and Animal Breeding

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Statistical and Computational ...... for Plant and Animal Breeding

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Statistical and Computational ...... for Plant and Animal Breeding

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Statistical and Computational ...... for Plant and Animal Breeding

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Statistical and Computational ...... for Plant and Animal Breeding

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P1476

Statistical and Computational ...... for Plant and Animal Breeding

@en

P2093

Robert J. Tempelman

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Statistical significance for genomewide studies

Applications of population genetics to animal breeding, from wright, fisher and lush to genomic prediction

Defining window-boundaries for genomic analyses using smoothing spline techniques

Parallel Markov chain Monte Carlo - bridging the gap to high-performance Bayesian computation in animal breeding and genetics

The Estimation of Environmental and Genetic Trends from Records Subject to Culling

Toward genomic prediction from whole-genome sequence data: impact of sequencing design on genotype imputation and accuracy of predictions.

A reaction norm model for genomic selection using high-dimensional genomic and environmental data

Microarray data analysis: from disarray to consolidation and consensus.

A variational Bayes algorithm for fast and accurate multiple locus genome-wide association analysis.

Semiparametric regression during 2003-2007.

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s13253-015-0225-2

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442-466

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scholarly article

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10.1007/S13253-015-0225-2

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http://www.w3.org/2001/XMLSchema#string

P478

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2015-09-28T00:00:00Z

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Amar