AndreaBozzo/ceres-open-data-index huggingface dataset:
Genomes To Fields 2015

<p>Phenotypic, genotypic, and environment data for the 2015 field season: The data is stored in <a href="http://datacommons.cyverse.org/browse/iplant/home/shared/commons_repo/curated/Carolyn_Lawrence_Dill_G2F_Mar_2017">CyVerse</a>.</p>
<p>Data types in this directory tree are: hybrid and inbred agronomic and performance traits; inbred genotypic data; and environmental (soil, weather) data collected from the Genomes To Fields (G2F) project cooperators. G2F is an umbrella initiative to support translation of maize (<em>Zea mays</em>) genomic information for the benefit of growers, consumers and society. This public-private partnership is building on publicly funded corn genome sequencing projects to develop approaches to understand the functions of corn genes and specific alleles across environments. Ultimately this information will be used to enable accurate prediction of the phenotypes of corn plants in diverse environments. There are many dimensions to the over-arching goal of understanding genotype-by-environment (GxE) interactions, including which genes impact which traits and trait components, how genes interact among themselves (GxG), the relevance of specific genes under different growing conditions, and how these genes influence plant growth during various stages of development. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: CyVerse Genomes To Fields 2015 dataset download.</p> <p>File Name: Web Page, url: <a href="http://datacommons.cyverse.org/browse/iplant/home/shared/commons_repo/curated/Carolyn_Lawrence_Dill_G2F_Mar_2017">http://datacommons.cyverse.org/browse/iplant/home/shared/commons_repo/curated/Carolyn_Lawrence_Dill_G2F_Mar_2017</a> </p><p>Dataset (csv) and metadata (BibTex, Endnote) data downloads. See _readme.txt for file contents.</p></li></ul><p></p>

Tags: ars, data-gov, g2f, genomes-by-environment, genomes-to-fields, gxe, np301
Organization: Department of Agriculture
CottonGen Synteny Viewer

<p>Conserved syntenic regions among publicly available cotton genomes were analyzed by CottonGen and made available using the Tripal Synteny Viewer developed by the Fei Bioinformatics Lab from the Boyce Thomson Institute at Cornell University. Analysis was done using MCScanX (Wang et al. 2012) with default settings and blast files were made using blastp with an expectation value cutoff < 1e-10,  maximum alignment of 5, and maximum scores of 5.</p>
<p>The synteny viewer displays all the conserved syntenic blocks between a selected chromosome of a genome and another genome in a circular and tabular layout. Once a block is chosen in the circular or tabular layout, all the genes in the block are shown in a graphic and tabular format. The gene names have hyperlinks to gene pages where detailed information of the gene can be accessed. The ‘synteny’ section of the gene page displays all the orthologs and the paralogs with link to the corresponding syntenic blocks or gene pages. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Website Pointer for Cottongen Synteny Viewer.</p> <p>File Name: Web Page, url: <a href="https://www.cottongen.org/synview/search">https://www.cottongen.org/synview/search</a> </p><p>Synteny among Cotton genomes can be viewed using the new Tripal Synteny Viewer. Conserved syntenic regions among publicly available cotton genomes were analyzed by CottonGen and made available using the Tripal Synteny Viewer developed by the Fei Bioinformatics Lab from the Boyce Thomson Institute at Cornell University. Analysis was done using MCScanX (Wang et al. 2012) with default settings and blast files were made using blastp with an expectation value cutoff < 1e-10,  maximum alignment of 5, and maximum scores of 5.</p>
<p>The synteny viewer dynamically displays all the conserved syntenic blocks between a selected chromosome of a genome and another genome in a circular and tabular layout. Once a block is chosen in the circular or tabular layout, all the genes in the block are shown in a graphic and tabular format. The gene names have hyperlinks to gene pages where detailed information of the gene can be accessed. The ‘synteny’ section of the gene page displays all the orthologs and the paralogs with link to the corresponding syntenic blocks or gene pages.</p>
<p></p></li></ul><p></p>

Tags: ars, cottongen, data-gov, np301, online-database, synteny-viewer, tripal
Organization: Department of Agriculture
Cligen

<p>Cligen is a stochastic weather generator which produces daily estimates of precipitation, temperature, dewpoint, wind, and solar radiation for a single geographic point, using monthly parameters (means, SD's, skewness, etc.) derived from the historic measurements. Unlike other climate generators, it produces individual storm parameter estimates, including time to peak, peak intensity, and storm duration, which are required to run the WEPP and the WEPS soil erosion models. Station parameter files to run Cligen for several thousand U. S. sites are available for download from this website: also data and software to build station files for international sites. With the exception of Tmin, Tmax, and Tdew temperatures (changed in January 2004), daily estimates for each parameter are generated independently of the others. With the current random number generator, subsequent runs on the same machine made with identical inputs will produce identical results.</p>
<p>Users of daily simulation models should consider the impacts of Cligen's characteristics on their application. Individual parameter distributions may be expected to reproduce monthly historic distributions quite well. However, if the model in question is sensitive to the daily interactions of two or more of the parameters Cligen produces, Cligen may not be the most appropriate weather generator to use. This is because for a given day, it generates solar radiation, and maximum and minimum temperatures completely independently from precipitation. Experience and common sense tell us that these parameters are NOT independent. In practice this may not be a huge issue, since it is not uncommon for models to be sensitive to one weather parameter on a daily basis, and relatively insensitive to the others, as long as their monthly trends are preserved. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Cligen.</p> <p>File Name: Web Page, url: <a href="https://www.ars.usda.gov/midwest-area/west-lafayette-in/national-soil-erosion-research/docs/wepp/cligen/">https://www.ars.usda.gov/midwest-area/west-lafayette-in/national-soil-erosion-research/docs/wepp/cligen/</a> </p><p>Overview, source code downloads, data files, and publications.</p></li></ul><p></p>

Tags: agricultural-research-service, australia, autumn, cleaning, climate-models, computer-software, computers, death, dewpoint, engineering, ganders, genes, idaho, indiana, meteorological-data, meteorology, models, oklahoma, people, prediction, quality-control, rain-intensity, runoff, simulation-models, soil-erosion, solar-radiation, statistical-analysis, stochastic-processes, storms, streams, temperature, united-states, usda-forest-service, water-erosion-prediction-project, wind
Organization: Department of Agriculture
Data from: Transcriptomic and functional resources for the Small Hive Beetle Aethina tumida, a worldwide parasite of honey bees

<p>Supplemental information from a project describing the transcriptome of a beetle parasite of honey bees</p>
<p>The small hive beetle (SHB), Aethina tumida, is a major pest of managed honey bee (Apis mellifera) colonies in the United States and Australia, and an emergent threat in Europe. While strong honey bee colonies generally keep SHB populations in check, weak or stressed colonies can succumb to infestations. This parasite has spread from a sub-Saharan Africa to three continents, leading to immense management and regulatory costs. We performed a transcriptomic analysis involving deep sequencing of multiple life stages and both sexes of this species. The assembled transcriptome appears to be nearly complete, as judged by conserved insect orthologs and the ability to find plausible homologs for 11,952 proteins described from the genome of the red flour beetle. Expressed genes include each of the major metabolic, developmental and sensory groups, along with genes for proteins involved with immune defenses and insecticide resistance. We also present a total of 23,085 high-quality SNP's for the assembled contigs. We highlight potential differences between this beetle and its honey bee hosts, and suggest mechanisms of future research into the biology and control of this species. SNP resources will allow functional genetic analyses and analyses of dispersal for this invasive pest. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: SHB_SuppTable3.</p> <p>File Name: SHB_SuppTable3.xlsx</p><p>Resource Description: Annotated transcript contigs</p></li><br><li><p>Resource Title: SHB_SuppTable2.</p> <p>File Name: SHB_SuppTable2.xlsx</p><p>Resource Description: SNP data file</p></li><br><li><p>Resource Title: SHB_SuppTable1.</p> <p>File Name: SHB_SuppTable1.xlsx</p><p>Resource Description: Microsatellite loci</p></li></ul><p></p>

Tags: aethina-tumida, ars, data-gov, hive-beetle, parasites
Organization: Department of Agriculture
PhenologyMMS

<p>PhenologyMMS is a simulation model that outlines and quantifies the developmental sequence of different crops under varying levels of water deficits, provides developmental information relevant to each crop, and is intended to be used either independently or inserted into existing crop growth models. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: PhenologyMMS.</p> <p>File Name: Web Page, url: <a href="https://www.ars.usda.gov/research/software/download/?softwareid=238&modecode=30-12-30-25">https://www.ars.usda.gov/research/software/download/?softwareid=238&modecode=30-12-30-25</a> </p><p>download page</p></li></ul><p></p>

Tags: algorithms, computer-software, corn, crop-management, crop-models, crops, cultivars, environmental-factors, field-experimentation, growth-and-development, hay, helianthus-annuus, hordeum-vulgare, models, panicum, panicum-miliaceum-subsp-miliaceum, phenology, plant-available-water, prediction, setaria-italica, simulation-models, soil-water, sorghum-bicolor, sorghum-poaceae, spring-barley, spring-wheat, triticum-aestivum, winter, winter-wheat, zea-mays
Organization: Department of Agriculture
Data from: Life history metrics for <i>Culex tarsalis </i>(Diptera: Culicidae) and <i>Culicoides sonorensis </i>(Diptera: Ceratopogonidae) are not impacted by artificial feeding on defibrinated versus EDTA-treated blood

<p dir="ltr">Artificial blood feeding is a common practice for the study and maintenance of blood-feeding arthropod colonies. Commercially purchased blood is often treated to prevent clot-formation using either mechanical or chemical means. For many hematophagous insects, the effect that different anticoagulation methods may have on life history metrics is unclear. In the current study, <i>Culex tarsalis</i> Coquillett and <i>Culicoides sonorensis</i> Wirth & Jones were fed blood treated with either mechanical (defibrination) or chemical (K2 EDTA) anticoagulation methods. Several blood feeding and life history metrics were evaluated between treatment groups including proportion blood feeding, fecundity, fertility, and mortality. No significant differences were found for any of the measured life history metrics for either species. For experiments measuring aspects of these blood feeding and life history traits, blood treated using either defibrination or K2 EDTA anticoagulants should not impact experimental outcomes. These studies were conducted using laboratory reared colony populations of <i>Culex tarsalis </i>and <i>Culicoides sonorensis</i>. The effect of these anticoagulation methods on life history metrics of field collected populations could be different.</p>

Tags: anticoagulants, ars, blood-feeding, culex, culicoides, data-gov
Organization: Department of Agriculture
Data from: Changes in genetic selection differentials and generation intervals in US Holstein dairy cattle as a result of genomic selection

<p>Aggregate means for six traits (milk, fat, and protein yields, somatic cell score, length of productive life, and daughter pregnancy rate) </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Holstein Milk Yield.</p> <p>File Name: HO_M.csv</p><p>Resource Description: Aggregate means of Holstein predicted breeding values for milk yield and birth dates</p></li><br><li><p>Resource Title: Holstein Fat Yield.</p> <p>File Name: HO_f.csv</p><p>Resource Description: Aggregate means of Holstein predicted breeding values for fat yield and birth dates</p></li><br><li><p>Resource Title: Holstein Protein Yield.</p> <p>File Name: HO_p.csv</p><p>Resource Description: Aggregate means of Holstein predicted breeding values for protein yield and birth dates</p></li><br><li><p>Resource Title: Holstein Somatic Cell Score.</p> <p>File Name: HO_scs.csv</p><p>Resource Description: Aggregate means of Holstein predicted breeding values for somatic cell score and birth dates</p></li><br><li><p>Resource Title: Holstein Productive Life.</p> <p>File Name: HO_pl.csv</p><p>Resource Description: Aggregate means of Holstein predicted breeding values for productive life and birth dates</p></li><br><li><p>Resource Title: Holstein Daughter Pregnancy Rate.</p> <p>File Name: HO_DPR.csv</p><p>Resource Description: Aggregate means of Holstein predicted breeding values for daughter pregnancy rate and birth dates</p></li><br><li><p>Resource Title: Data Dictionary.</p> <p>File Name: data_dictionary.csv</p><p>Resource Description: Defines variables / sub-components with examples as used in column headers.  Filenames:  </p>
<ul>
<li>Holstein Productive Life: HO_pl.csv</li>
<li>Holstein Daughter Pregnancy Rate: HO_DPR.csv</li>
<li>Holstein Somatic Cell Score: HO_scs.csv</li>
<li>Holstein Protein Yield: HO_p.csv</li>
<li>Holstein Fat Yield: HO_f.csv</li>
<li>Holstein Milk Yield: HO_M.csv</li></ul><p></p></li>
</ul>

Tags: ars, bulls, cows, dairy-cattle, data-gov, genetic-improvement, genetic-traits, genetic-trend, heritability, holstein, marker-assisted-selection, milk, np101, sires
Organization: Department of Agriculture
CottonGen Map Viewer

<p>MapViewer is a graphical tool for viewing and comparing  <em>Gossypium</em> spp. genetic maps. It includes dynamically scrollable maps, correspondence matrices, dot plots, links to details about map features, and exporting functionality. It was developed by the MainLab at Washington State University and is available for download for use in other Tripal databases. The query interface allows the user to select Species, Map, and Linkage Group options. Help information includes a video tutorial, user manual, and sample map, correspondence matrix, dot plot, and exported figures.</p>
<div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Website Pointer for CottonGen Map Viewer.</p> <p>File Name: Web Page, url: <a href="https://www.cottongen.org/MapViewer" target="_blank">https://www.cottongen.org/MapViewer</a> </p><p>MapViewer is a graphical tool for viewing and comparing *Gossypium* spp. genetic maps. It includes dynamically scrollable maps, correspondence matrices, dot plots, links to details about map features, and exporting functionality. It was developed by the MainLab at Washington State University and is available for download for use in other Tripal databases. The query interface allows the user to select Species, Map, and Linkage Group options. Help information includes a video tutorial, user manual, and sample map, correspondence matrix, dot plot, and exported figures.</p></li></ul>

Tags: ars, cottongen, data-gov, map-viewer, np301, online-database
Organization: Department of Agriculture
CottonGen Primer3

<p>Primer3web version 4.0.0 allows users to pick PCR primers from a DNA sequence based on criteria including:</p>
<ul>
<li>
<p>oligonucleotide melting temperature, size, GC content, and primer-dimer possibilities,</p>
</li>
<li>
<p>PCR product size,</p>
</li>
<li>
<p>positional constraints within the source (template) sequence, and</p>
</li>
<li>
<p>possibilities for ectopic priming (amplifying the wrong sequence)</p>
</li>
<li>
<p>many other constraints.</p>
</li>
</ul>
<p>All of these criteria are user-specifiable as constraints, and some are specifiable as terms in an objective function that characterizes an optimal primer pair.</p>
<div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Website Pointer for CottonGen Primer3.</p> <p>File Name: Web Page, url: <a href="https://www.cottongen.org/tools/primer3" target="_blank">https://www.cottongen.org/tools/primer3</a> </p></li></ul>

Tags: ars, cottongen, data-gov, np301, online-database, primer3
Organization: Department of Agriculture
Sodium Monitoring Dataset

<p>The Agricultural Research Service of the US Department of Agriculture (USDA) in collaboration with other government agencies has a program to track changes in the sodium content of commercially processed and restaurant foods. This monitoring program includes these activities: </p>
<ul>
<li>Tracking sodium levels of ~125 popular foods, called "<a href="https://www.ars.usda.gov/Services/Docs.htm?docid=22872 ">Sentinel Foods</a>," by periodically sampling them at stores and restaurants around the country, followed by laboratory analyses.</li>
<li>Tracking levels of "related" nutrients that could change when manufacturers reformulate their foods to reduce sodium; these related nutrients are potassium, total and saturated fat, total dietary fiber, and total sugar.</li>
<li>Sharing the results of these monitoring activities to the public periodically in the <a href="https://www.ars.usda.gov/ARSUserFiles/80400525/Sodium/Copy of SodiumMonitoringDatasetUpdatedJuly2616.xlsx">Sodium Monitoring Dataset</a> and <a href="https://www.ars.usda.gov/Services/docs.htm?docid=8964">USDA National Nutrient Database for Standard Reference</a> and once every two years in the <a href="https://www.ars.usda.gov/Services/docs.htm?docid=12068">Food and Nutrient Database for Dietary Studies</a>.</li>
</ul>
<p>The Sodium Monitoring Dataset is downloadable in Excel spreadsheet format. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Data Dictionary.</p> <p>File Name: SodiumMonitoringDataset_datadictionary.csv</p><p>Resource Description: Defines variables, descriptions, data types, character length, etc. for each of the spreadsheets in this Excel data file: Sentinel Foods - Baseline; Priority-2 Foods - Baseline; Sentinel Foods - Monitoring; Priority-2 Foods - Monitoring.</p></li><br><li><p>Resource Title: Sodium Monitoring Dataset (MS Excel download).</p> <p>File Name: SodiumMonitoringDatasetUpdatedJuly2616.xlsx</p><p>Resource Description: Microsoft Excel : Sentinel Foods - Baseline; Priority-2 Foods - Baseline; Sentinel Foods - Monitoring; Priority Foods - Monitoring.</p></li></ul><p></p>

Tags: ars, data-gov, food-composition, food-consumption, np107
Organization: Department of Agriculture
Dairy Gas Emissions Model (DairyGEM)

<p>The Dairy Gas Emissions Model (DairyGEM)  uses process level simulation and process related emission factors to predict ammonia, hydrogen sulfide, VOC and greenhouse gas emissions along with the carbon, energy and water footprints of dairy production systems. A process-based simulation is used to predict ammonia, hydrogen sulfide, and VOC emissions as influenced by climate and farm management. Net carbon dioxide, methane, and nitrous oxide emissions are also estimated using process simulation or process related emission factors. Environmental footprints are determined that include both primary and secondary sources. Primary sources occur during the farm production process and secondary sources are those occurring during the production of resources used including machinery, fuel, electricity, fertilizer, pesticides, and plastic. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Dairy Gas Emissions Model - home.</p> <p>File Name: Web Page, url: <a href="https://www.ars.usda.gov/northeast-area/up-pa/pswmru/docs/dairy-gas-emissions-model/">https://www.ars.usda.gov/northeast-area/up-pa/pswmru/docs/dairy-gas-emissions-model/</a> </p><p>Provides description of the DairyGEM model with links to reference manual, download instructions, and training video module.</p></li></ul><p></p>

Tags: ars, dairygem, data-gov
Organization: Department of Agriculture
Data from: Clarireedia: A new fungal genus comprising four pathogenic species responsible for dollar spot disease of turfgrass

<p>Dollar spot is one of the most destructive globally distributed diseases of turfgrass.  The identity of the fungus responsible for the disease has been the subject of debate for more than 75 years.  These datasets provide the phylogenetic evidence from three nucleotide sequence markers (CaM, ITS and Mcm7) that underlie the establishment of the new fungal genus <em>Clarireedia</em>, which includes four species that cause turfgrass dollar spot disease: <em>Clarireedia homoeocarpa</em>, <em>C. bennettii</em>, <em>C. jacksonii</em>, and <em>C. monteithiana</em>.  Datasets include the DNA sequence alignments for the CaM, ITS and Mcm7 markers for exemplar <em>Clarireedia</em> isolates, and the complete combined phylogenetic dataset and phylogenetic tree file. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: DNA sequence alignment, combined dataset.</p> <p>File Name: Allgenes_alignment.txt</p></li><br><li><p>Resource Title: Phylogenetic tree file.</p> <p>File Name: Allgenes_phylogeny<em>MrBayes.nex</em>.con<em>.tre</em>.txt</p><p>Resource Description: Derived from analysis of DNA sequence alignment</p></li><br><li><p>Resource Title: DNA sequence alignment of CaM marker for dollar spot fungi exemplars.</p> <p>File Name: CaM_DS_diagnostic sites.txt</p></li><br><li><p>Resource Title: DNA sequence alignment of ITS marker for dollar spot fungi exemplars.</p> <p>File Name: ITS_DS_diagnostic sites.txt</p></li><br><li><p>Resource Title: DNA sequence alignment of Mcm7 marker for dollar spot fungi exemplars.</p> <p>File Name: Mcm7_DS_diagnostic sites.txt</p></li></ul><p></p>

Tags: ars, ascomycetous-fungi, clarireedia, clarireedia-bennettii, clarireedia-homoeocarpa, clarireedia-jacksonii, clarireedia-monteithiana, data-gov, np303, phylogenetic, plant-disease, turfgrass
Organization: Department of Agriculture