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Including explicit marker-by-environment interaction for large-scale genomic prediction

Arne De Coninck, Drosos Kourounis, Fabio Verbosio, Olaf Schenk, Bernard De Baets UGent, Steven Maenhout UGent and Jan Fostier UGent (2015) COMMUNICATIONS IN AGRICULTURAL AND APPLIED BIOLOGICAL SCIENCES. 80(1). p.117-121
abstract
Genomic prediction for plants is heavily influenced by the environment. Not only do the environmental conditions influence the phenotypic traits directly, genetic effects may also vary across different environments. Therefore, it is essential to include marker-by-environment interactions in the linear mixed models used for analyzing the genomic data. However, when every genetic marker is coupled to every environmental covariate, the problem size grows dramatically. Luckily, information about marker-by-environment interaction is only sparsely present in data sets, since each plant is tested in a limited number of environmental conditions only. In contrast, the genotypes of plants are a dense source of information and thus including marker effects and their interaction with environment in a single-step genomic prediction setting requires the coupling of sparse and dense matrix algebra. Our implementation of this strategy uses distributed computing techniques together with an optimized library for sparse matrix manipulations (PARDISO) to efficiently use a high performance computing cluster for the analysis of large-scale data sets.
Please use this url to cite or link to this publication:
author
organization
year
type
conference
publication status
published
subject
keyword
genomic prediction, high performance computing, marker-by-environment interaction
in
COMMUNICATIONS IN AGRICULTURAL AND APPLIED BIOLOGICAL SCIENCES
Comm. Agric. Appl. Biol. Sci.
editor
Xavier Draye
volume
80
issue
1
pages
117 - 121
conference name
20th National symposium on Applied Biological Sciences
conference location
Louvain-La-Neuve, Belgium
conference start
2015-01-30
conference end
2015-01-30
ISSN
1379-1176
project
HPC-UGent: the central High Performance Computing infrastructure of Ghent University
project
Bioinformatics: from nucleotids to networks (N2N)
language
English
UGent publication?
yes
classification
C1
copyright statement
I have transferred the copyright for this publication to the publisher
id
5929345
handle
http://hdl.handle.net/1854/LU-5929345
date created
2015-04-09 09:59:56
date last changed
2016-12-19 15:36:33
@inproceedings{5929345,
  abstract     = {Genomic prediction for plants is heavily influenced by the environment. Not only do the environmental conditions influence the phenotypic traits directly, genetic effects may also vary across different environments. Therefore, it is essential to include marker-by-environment interactions in the linear mixed models used for analyzing the genomic data. However, when every genetic marker is coupled to every environmental covariate, the problem size grows dramatically. Luckily, information about marker-by-environment interaction is only sparsely present in data sets, since each plant is tested in a limited number of environmental conditions only. In contrast, the genotypes of plants are a dense source of information and thus including marker effects and their interaction with environment in a single-step genomic prediction setting requires the coupling of sparse and dense matrix algebra. Our implementation of this strategy uses distributed computing techniques together with an optimized library for sparse matrix manipulations (PARDISO) to efficiently use a high performance computing cluster for the analysis of large-scale data sets.},
  author       = {De Coninck, Arne and Kourounis, Drosos and Verbosio, Fabio and Schenk, Olaf and De Baets, Bernard and Maenhout, Steven and Fostier, Jan},
  booktitle    = {COMMUNICATIONS IN AGRICULTURAL AND APPLIED BIOLOGICAL SCIENCES},
  editor       = {Draye, Xavier},
  issn         = {1379-1176},
  keyword      = {genomic prediction,high performance computing,marker-by-environment interaction},
  language     = {eng},
  location     = {Louvain-La-Neuve, Belgium},
  number       = {1},
  pages        = {117--121},
  title        = {Including explicit marker-by-environment interaction for large-scale genomic prediction},
  volume       = {80},
  year         = {2015},
}

Chicago
De Coninck, Arne, Drosos Kourounis, Fabio Verbosio, Olaf Schenk, Bernard De Baets, Steven Maenhout, and Jan Fostier. 2015. “Including Explicit Marker-by-environment Interaction for Large-scale Genomic Prediction.” In Communications in Agricultural and Applied Biological Sciences, ed. Xavier Draye, 80:117–121.
APA
De Coninck, A., Kourounis, D., Verbosio, F., Schenk, O., De Baets, B., Maenhout, S., & Fostier, J. (2015). Including explicit marker-by-environment interaction for large-scale genomic prediction. In X. Draye (Ed.), COMMUNICATIONS IN AGRICULTURAL AND APPLIED BIOLOGICAL SCIENCES (Vol. 80, pp. 117–121). Presented at the 20th National symposium on Applied Biological Sciences.
Vancouver
1.
De Coninck A, Kourounis D, Verbosio F, Schenk O, De Baets B, Maenhout S, et al. Including explicit marker-by-environment interaction for large-scale genomic prediction. In: Draye X, editor. COMMUNICATIONS IN AGRICULTURAL AND APPLIED BIOLOGICAL SCIENCES. 2015. p. 117–21.
MLA
De Coninck, Arne, Drosos Kourounis, Fabio Verbosio, et al. “Including Explicit Marker-by-environment Interaction for Large-scale Genomic Prediction.” Communications in Agricultural and Applied Biological Sciences. Ed. Xavier Draye. Vol. 80. 2015. 117–121. Print.