@article{
 title = {Rice Galaxy: an open resource for plant science},
 type = {article},
 year = {2019},
 pages = {1-14},
 volume = {8},
 websites = {http://orcid.org/0000-0001-8512-144X},
 id = {1dcdb9df-e76f-384c-9ed4-5838d0a0cad7},
 created = {2020-04-22T21:44:57.004Z},
 accessed = {2020-04-21},
 file_attached = {true},
 profile_id = {42d295c0-0737-38d6-8b43-508cab6ea85d},
 last_modified = {2020-05-11T14:43:33.687Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 citation_key = {Juanillas2019},
 private_publication = {false},
 abstract = {Background: Rice molecular genetics, breeding, genetic diversity, and allied research (such as rice-pathogen interaction) have adopted sequencing technologies and high-density genotyping platforms for genome variation analysis and gene discovery. Germplasm collections representing rice diversity, improved varieties, and elite breeding materials are accessible through rice gene banks for use in research and breeding, with many having genome sequences and high-density genotype data available. Combining phenotypic and genotypic information on these accessions enables genome-wide association analysis, which is driving quantitative trait loci discovery and molecular marker development. Comparative sequence analyses across quantitative trait loci regions facilitate the discovery of novel alleles. Analyses involving DNA sequences and large genotyping matrices for thousands of samples, however, pose a challenge to non−computer savvy rice researchers. Findings: The Rice Galaxy resource has shared datasets that include high-density genotypes from the 3,000 Rice Genomes project and sequences with corresponding annotations from 9 published rice genomes. The Rice Galaxy web server and deployment installer includes tools for designing single-nucleotide polymorphism assays, analyzing genome-wide association studies, population diversity, rice−bacterial pathogen diagnostics, and a suite of published genomic prediction methods.},
 bibtype = {article},
 author = {Juanillas, Venice and Dereeper, Alexis and Beaume, Nicolas and Droc, Gaetan and Dizon, Joshua and Mendoza, John Robert and Perdon, Jon Peter and Mansueto, Locedie and Triplett, Lindsay and Lang, Jillian and Zhou, Gabriel and Ratharanjan, Kunalan and Plale, Beth and Haga, Jason and Leach, Jan E and Ruiz, Manuel and Thomson, Michael and Alexandrov, Nickolai and Larmande, Pierre and Kretzschmar, Tobias and Mauleon, Ramil P},
 doi = {10.1093/gigascience/giz028}
}

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Germplasm collections representing rice diversity, improved varieties, and elite breeding materials are accessible through rice gene banks for use in research and breeding, with many having genome sequences and high-density genotype data available. Combining phenotypic and genotypic information on these accessions enables genome-wide association analysis, which is driving quantitative trait loci discovery and molecular marker development. Comparative sequence analyses across quantitative trait loci regions facilitate the discovery of novel alleles. Analyses involving DNA sequences and large genotyping matrices for thousands of samples, however, pose a challenge to non−computer savvy rice researchers. Findings: The Rice Galaxy resource has shared datasets that include high-density genotypes from the 3,000 Rice Genomes project and sequences with corresponding annotations from 9 published rice genomes. 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