Nti-Addae Y. auteur aut IRD Matthews D. auteur aut IRD Ulat V. J. auteur aut IRD Syed R. auteur aut IRD Sempere G. auteur aut IRD Petel A. auteur aut IRD Renner J. auteur aut IRD Larmande Pierre auteur aut IRD Guignon V. auteur aut IRD Jones E. auteur aut IRD Robbins K. auteur aut IRD text journalArticle eng text/pdf reformatted digital access Motivation: 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. Results: We found that data extract times are greatly influenced by the orientation in which genotype data is stored in a system. HDF5 consistently performed best, in part because it can more efficiently work with both orientations of the allele matrix. specialized 122 020 baz096 [10p.] 2019 1758-0463 https://www.documentation.ird.fr/hor/fdi:010077059 10.1093/database/baz096 1758-0463 [F B010077059] https://www.documentation.ird.fr/hor/fdi:010077059 https://horizon.documentation.ird.fr/exl-doc/pleins_textes/divers19-10/010077059.pdf IRD - Base Horizon / Pleins textes 2019-11-05 2019-11-07 fdi:010077059 fre