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Dataset Title:  Metagenomic, metatranscriptomic, and single cell sequencing data from an
Environmental Sample Processor deployment in Monterey Bay, CA in 2016.
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_753343)
Range: longitude = -121.901 to -121.901°E, latitude = 36.835 to 36.835°N
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Subset | Data Access Form | Files
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Y Axis: 
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 distinct() ?
? ("Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.")
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Things You Can Do With Your Graphs

Well, you can do anything you want with your graphs, of course. But some things you might not have considered are:

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  GOLD_Project_ID {
    String bcodmo_name "accession number";
    String description "Accession number at DOE JGI IMG database: https://img.jgi.doe.gov";
    String long_name "GOLD Project ID";
    String units "unitless";
  Analysis_Project_Name {
    String bcodmo_name "project";
    String description "Name of sequencing project";
    String long_name "Analysis Project Name";
    String units "unitless";
  Type {
    String bcodmo_name "sample_descrip";
    String description "Material type sequenced";
    String long_name "Type";
    String units "unitless";
  Assembly_Method {
    String bcodmo_name "sampling_method";
    String description "assembly method";
    String long_name "Assembly Method";
    String units "unitless";
  Collection_Date {
    String bcodmo_name "date";
    String description "collection date of samples";
    String long_name "Collection Date";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String units "unitless";
  Instrument {
    String bcodmo_name "instrument";
    String description "instrument";
    String long_name "Instrument";
    String units "unitless";
  JGI_Contigs_Link {
    String bcodmo_name "unknown";
    String description "JGI Contigs Link";
    String long_name "JGI Contigs Link";
    String units "unitless";
  JGI_Project_ID {
    Int32 _FillValue 2147483647;
    Int32 actual_range 1174504, 1190880;
    String bcodmo_name "unknown";
    String description "JGI Project ID";
    String long_name "JGI Project ID";
    String units "unitless";
  JGI_Sample_ID {
    Int32 _FillValue 2147483647;
    Int32 actual_range 166736, 178378;
    String bcodmo_name "sample";
    String description "JGI Sample ID";
    String long_name "JGI Sample ID";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  JGI_Sequencing_Project_ID {
    Int32 _FillValue 2147483647;
    Int32 actual_range 1174680, 1190883;
    String bcodmo_name "unknown";
    String description "JGI Sequencing Project ID";
    String long_name "JGI Sequencing Project ID";
    String units "unitless";
  JGI_Sequencing_Project_Name {
    String bcodmo_name "unknown";
    String description "JGI Sequencing Project Name";
    String long_name "JGI Sequencing Project Name";
    String units "unitless";
  Latitude_and_Longitude {
    String bcodmo_name "unknown";
    String description "Latitude and Longitude";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "unitless";
  NCBI_BioProject_Accession {
    String bcodmo_name "unknown";
    String description "NCBI BioProject Accession";
    String long_name "NCBI Bio Project Accession";
    String units "unitless";
  NCBI_BioSample_Accession {
    String bcodmo_name "unknown";
    String description "NCBI BioSample Accession";
    String long_name "NCBI Bio Sample Accession";
    String units "unitless";
  NCBI_Project_ID {
    Int32 _FillValue 2147483647;
    Int32 actual_range 467720, 511331;
    String bcodmo_name "unknown";
    String description "NCBI Project ID";
    String long_name "NCBI Project ID";
    String units "unitless";
  NCBI_SRA_Accession_ID {
    String bcodmo_name "unknown";
    String description "NCBI SRA Accession ID";
    String long_name "NCBI SRA Accession ID";
    String units "unitless";
  Sample_Name {
    String bcodmo_name "sample";
    String description "sample name";
    String long_name "Sample Name";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  Sequencing_Run_Mode {
    String bcodmo_name "unknown";
    String description "sequencing run mode";
    String long_name "Sequencing Run Mode";
    String units "unitless";
  Total_Bases {
    String bcodmo_name "unknown";
    String description "total bases";
    String long_name "Total Bases";
    String units "unitless";
  Volume_Seawater_Filtered {
    Float32 _FillValue NaN;
    Float32 actual_range 73.5, 1000.0;
    String bcodmo_name "vol_filt";
    String description "Volume Seawater Filtered";
    String long_name "Volume Seawater Filtered";
    String units "milliliters (mL)";
  env_biome {
    String bcodmo_name "unknown";
    String description "environmental biome";
    String long_name "Env Biome";
    String units "unitless";
  env_feature {
    String bcodmo_name "unknown";
    String description "environmental feature";
    String long_name "Env Feature";
    String units "unitless";
  env_material {
    String bcodmo_name "unknown";
    String description "environmental material";
    String long_name "Env Material";
    String units "unitless";
  geo_loc_name {
    String bcodmo_name "unknown";
    String description "location name";
    String long_name "Geo Loc Name";
    String units "unitless";
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 36.835, 36.835;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "latitude with positive values indicating North";
    String ioos_category "Location";
    String long_name "Latitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LATX/";
    String standard_name "latitude";
    String units "degrees_north";
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range -121.901, -121.901;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "longitude with negative values indicating West";
    String ioos_category "Location";
    String long_name "Longitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LONX/";
    String standard_name "longitude";
    String units "degrees_east";
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"The Environmental Sample Processor (ESP) filtered seawater sequentially
through 5.0 um and 0.2 um pore size polyvinylidene fluoride filters. Seawater
was evacuated from filters and followed twice with a 2 minute incubation with
1 ml of RNAlater\\u2122. RNAlater was evacuated, and filters were stored in the
ESP until they were transferred to -80 C upon instrument recovery.\\u00a0
Grab samples for sequencing while the ESP was not deployed were taken using
Niskin bottles that collected seawater at the same depth and location of the
ESP. Water was transferred to a low-density polyethylene cubitainer and
maintained at ambient temperature until return to lab within 30 min. Seawater
was filtered as above with vacuum filtration and preserved immediately in
liquid nitrogen and transferred to -80 C.
Single-cell sequencing: Seawater was transferred directly from the Niskin
bottle to a 50 ml Falcon tube and placed on ice until brought back to lab.
Each sampling day, 3 x 1 ml of seawater was preserved in cryovials using 100
ul of glyTe (5 ml glycerol, 3 ml Milli-Q H2O, 1 ml 100 x TE pH 8.0, 0.2 um
filter sterilized after mixing the above, and stored in -20 C freezer).
Preserved samples were then placed in a -80 C freezer. Samples were processed
and sequenced at JGI";
    String awards_0_award_nid "541254";
    String awards_0_award_number "OCE-1342694";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1342694";
    String awards_0_funder_name "NSF Division of Ocean Sciences";
    String awards_0_funding_acronym "NSF OCE";
    String awards_0_funding_source_nid "355";
    String awards_0_program_manager "David L. Garrison";
    String awards_0_program_manager_nid "50534";
    String cdm_data_type "Other";
    String comment 
"Metagenomic, metatranscriptomic, and single cell sequencing data from the Fall 2016 ESP deployment in Monterey Bay, CA 
  PI: Mary Ann Moran 
  Version: 2020-03-10";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_email "info@bco-dmo.org";
    String creator_name "BCO-DMO";
    String creator_type "institution";
    String creator_url "https://www.bco-dmo.org/";
    String data_source "extract_data_as_tsv version 2.3  19 Dec 2019";
    String date_created "2019-01-22T20:12:37Z";
    String date_modified "2020-04-01T17:17:54Z";
    String defaultDataQuery "&time<now";
    String doi "10.26008/1912/bco-dmo.753343.2";
    Float64 Easternmost_Easting -121.901;
    Float64 geospatial_lat_max 36.835;
    Float64 geospatial_lat_min 36.835;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -121.901;
    Float64 geospatial_lon_min -121.901;
    String geospatial_lon_units "degrees_east";
    String history 
"2020-12-02T12:45:43Z (local files)
2020-12-02T12:45:43Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_753343.das";
    String infoUrl "https://www.bco-dmo.org/dataset/753343";
    String institution "BCO-DMO";
    String keywords "accession, analysis, Analysis_Project_Name, assembly, Assembly_Method, bases, bco, bco-dmo, bio, biological, biome, chemical, collection, Collection_Date, contigs, data, dataset, date, dmo, env, env_biome, env_feature, env_material, erddap, feature, filtered, geo, geo_loc_name, gold, GOLD_Project_ID, instrument, jgi, JGI_Contigs_Link, JGI_Project_ID, JGI_Sample_ID, JGI_Sequencing_Project_ID, JGI_Sequencing_Project_Name, latitude, Latitude_and_Longitude, link, loc, longitude, management, material, method, mode, name, ncbi, NCBI_BioProject_Accession, NCBI_BioSample_Accession, NCBI_Project_ID, NCBI_SRA_Accession_ID, oceanography, office, preliminary, project, run, sample, Sample_Name, sea, seawater, sequencing, Sequencing_Run_Mode, sra, total, Total_Bases, type, volume, Volume_Seawater_Filtered, water";
    String license "https://www.bco-dmo.org/dataset/753343/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/753343";
    Float64 Northernmost_Northing 36.835;
    String param_mapping "{'753343': {'lat': 'flag - latitude', 'lon': 'flag - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/753343/parameters";
    String people_0_affiliation "University of Georgia";
    String people_0_affiliation_acronym "UGA";
    String people_0_person_name "Mary Ann Moran";
    String people_0_person_nid "51592";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of Georgia";
    String people_1_affiliation_acronym "UGA";
    String people_1_person_name "Brent Nowinski";
    String people_1_person_nid "662396";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "Woods Hole Oceanographic Institution";
    String people_2_affiliation_acronym "WHOI BCO-DMO";
    String people_2_person_name "Mathew Biddle";
    String people_2_person_nid "708682";
    String people_2_role "BCO-DMO Data Manager";
    String people_2_role_type "related";
    String project "OceanSulfurFluxBact";
    String projects_0_acronym "OceanSulfurFluxBact";
    String projects_0_description 
"Surface ocean bacterioplankton preside over a divergence point in the marine sulfur cycle where the fate of dimethylsulfoniopropionate (DMSP) is determined. While it is well recognized that this juncture influences the fate of sulfur in the ocean and atmosphere, its regulation by bacterioplankton is not yet understood. Based on recent findings in biogeochemistry, bacterial physiology, bacterial genetics, and ocean instrumentation, the microbial oceanography community is poised to make major advances in knowledge of this control point. This research project is ascertaining how the major taxa of bacterial DMSP degraders in seawater regulate DMSP transformations, and addresses the implications of bacterial functional, genetic, and taxonomic diversity for global sulfur cycling.
The project is founded on the globally important function of bacterial transformation of the ubiquitous organic sulfur compound DMSP in ocean surface waters. Recent genetic discoveries have identified key genes in the two major DMSP degradation pathways, and the stage is now set to identify the factors that regulate gene expression to favor one or the other pathway during DMSP processing. The taxonomy of the bacteria mediating DMSP cycling has been deduced from genomic and metagenomic sequencing surveys to include four major groups of surface ocean bacterioplankton. How regulation of DMSP degradation differs among these groups and maps to phylogeny in co-occurring members is key information for understanding the marine sulfur cycle and predicting its function in a changing ocean. Using model organism studies, microcosm experiments (at Dauphin Island Sea Lab, AL), and time-series field studies with an autonomous sample collection instrument (at Monterey Bay, CA), this project is taking a taxon-specific approach to decipher the regulation of bacterial DMSP degradation.
This research addresses fundamental questions of how the diversity of microbial life influences the geochemical environment of the oceans and atmosphere, linking the genetic basis of metabolic potential to taxonomic diversity. The project is training graduate students and post-doctoral scholars in microbial biodiversity and providing research opportunities and mentoring for undergraduate students. An outreach program is enhance understanding of the role and diversity of marine microorganisms in global elemental cycles among high school students. Advanced Placement Biology students are participating in marine microbial research that covers key learning goals in the AP Biology curriculum. Two high school students are selected each year for summer research internships in PI laboratories.";
    String projects_0_end_date "2018-12";
    String projects_0_name "Bacterial Taxa that Control Sulfur Flux from the Ocean to the Atmosphere";
    String projects_0_project_nid "541255";
    String projects_0_start_date "2014-01";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 36.835;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String subsetVariables "latitude,longitude";
    String summary "These metagenomic and metatranscriptomic time-series data cover a 52-day period in the fall of 2016 during an intense bloom of the dinoflagellate Akashiwo sanguinea in Monterey Bay, CA, USA. The dataset comprises 84 metagenomes, 82 metatranscriptomes, and 88 16S rRNA amplicon libraries that capture the functions and taxonomy the bacterial and archaeal community. In addition, 88 18S rRNA amplicon libraries describe the taxonomy of the eukaryotic community during the bloom. Microbial cells were collected at station M0 using the moored autonomous robotic Environmental Sample Processor (ESP) instrument and preserved with RNAlater in the instrument until retrieval.";
    String title "Metagenomic, metatranscriptomic, and single cell sequencing data from an Environmental Sample Processor deployment in Monterey Bay, CA in 2016.";
    String version "2";
    Float64 Westernmost_Easting -121.901;
    String xml_source "osprey2erddap.update_xml() v1.3";


Using tabledap to Request Data and Graphs from Tabular Datasets

tabledap lets you request a data subset, a graph, or a map from a tabular dataset (for example, buoy data), via a specially formed URL. tabledap uses the OPeNDAP (external link) Data Access Protocol (DAP) (external link) and its selection constraints (external link).

The URL specifies what you want: the dataset, a description of the graph or the subset of the data, and the file type for the response.

Tabledap request URLs must be in the form
For example,
Thus, the query is often a comma-separated list of desired variable names, followed by a collection of constraints (e.g., variable<value), each preceded by '&' (which is interpreted as "AND").

For details, see the tabledap Documentation.

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