Benchmarking database systems for Genomic Selection implementation
Author(s) -
Y.A. Nti-Addae,
Dave Matthews,
Victor Jun Ulat,
Raza M. Syed,
Guilhem Sempéré,
Adrien Pétel,
Jon Renner,
Pierre Larmande,
Valentin Guig,
Elizabeth Jones,
Kelly R. Robbins
Publication year - 2019
Publication title -
database
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 1.406
H-Index - 62
ISSN - 1758-0463
DOI - 10.1093/database/baz096
Subject(s) - benchmarking , selection (genetic algorithm) , computer science , database , genomic selection , world wide web , information retrieval , data science , business , artificial intelligence , biology , biochemistry , marketing , genotype , gene , single nucleotide polymorphism
With high-throughput genotyping systems now available, it has become feasible to fully integrate genotyping information into breeding programs. To make use of this information effectively requires DNA extraction facilities and marker production facilities that can efficiently deploy the desired set of markers across samples with a rapid turnaround time that allows for selection before crosses needed to be made. In reality, breeders often have a short window of time to make decisions by the time they are able to collect all their phenotyping data and receive corresponding genotyping data. This presents a challenge to organize information and utilize it in downstream analyses to support decisions made by breeders. In order to implement genomic selection routinely as part of breeding programs, one would need an efficient genotyping data storage system. We selected and benchmarked six popular open-source data storage systems, including relational database management and columnar storage systems.
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