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Dataset Title:  Accession numbers for raw sequences associated with field collections &
microcosms, 2015 and 2016
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_739077)
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Data Access Form | Files
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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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(Please be patient. It may take a while to get the data.)
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    [The graph you specified. Please be patient.]


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 {
  BioProject {
    String bcodmo_name "accession number";
    String description "NCBI GenBank BioProject accession number";
    String long_name "Bio Project";
    String units "unitless";
  study {
    String bcodmo_name "exp_type";
    String description "type of study";
    String long_name "Study";
    String units "unitless";
  sample_description {
    String bcodmo_name "sample_descrip";
    String description "description of samples";
    String long_name "Sample Description";
    String units "unitless";
  year {
    Int16 _FillValue 32767;
    Int16 actual_range 2015, 2016;
    String bcodmo_name "year";
    String description "year of sample collection";
    String long_name "Year";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/YEARXXXX/";
    String units "unitless";
  num_sequences {
    Byte _FillValue 127;
    Byte actual_range 57, 125;
    String bcodmo_name "count";
    String description "number of sequences";
    String long_name "Num Sequences";
    String units "unitless";
  NCBI_link {
    String bcodmo_name "external_link";
    String description "link to BioProject page at NCBI GenBank";
    String long_name "NCBI Link";
    String units "unitless";
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"Samples were collected as part of collections and experiments conducted at
Looe Key reef microcosm experiments (2015 and 2016) and field collections
(2016) in the Florida Keys National Marine Sanctuary (as described in other
datasets with this project).
Samples (1 L) were prefiltered (2 um), concentrated on to 0.22 um filters, DNA
extracted, and 16S rRNA in the V4 region amplified using 515F/806R primers
with barcodes on both ends. Sequencing was conducted using Illumina MiSeq
paired-end 250 chemistry.";
    String awards_0_award_nid "553932";
    String awards_0_award_number "OCE-1357423";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1357423";
    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 "Michael E. Sieracki";
    String awards_0_program_manager_nid "50446";
    String cdm_data_type "Other";
    String comment 
"Community 16S rRNA gene sequences 
   Accession numbers for raw sequences associated with field collections & microcosms (2015 and 2016) 
    Saharan dust deposition and bacterioplankton in marine surface water 
   PI's: E. Lipp, E. Ottesen (UGA) 
   version: 2018-06-19";
    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 dataset_current_state "Final and no updates";
    String date_created "2018-06-20T14:00:52Z";
    String date_modified "2020-06-03T14:21:28Z";
    String defaultDataQuery "&time<now";
    String doi "10.26008/1912/bco-dmo.739077.1";
    String history 
"2020-08-07T23:19:10Z (local files)
2020-08-07T23:19:10Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_739077.das";
    String infoUrl "https://www.bco-dmo.org/dataset/739077";
    String institution "BCO-DMO";
    String instruments_0_acronym "Automated Sequencer";
    String instruments_0_dataset_instrument_nid "739091";
    String instruments_0_description "General term for a laboratory instrument used for deciphering the order of bases in a strand of DNA. Sanger sequencers detect fluorescence from different dyes that are used to identify the A, C, G, and T extension reactions. Contemporary or Pyrosequencer methods are based on detecting the activity of DNA polymerase (a DNA synthesizing enzyme) with another chemoluminescent enzyme. Essentially, the method allows sequencing of a single strand of DNA by synthesizing the complementary strand along it, one base pair at a time, and detecting which base was actually added at each step.";
    String instruments_0_instrument_name "Automated DNA Sequencer";
    String instruments_0_instrument_nid "649";
    String instruments_0_supplied_name "Illumina MiSeq";
    String instruments_1_acronym "Thermal Cycler";
    String instruments_1_dataset_instrument_nid "739090";
    String instruments_1_description 
"General term for a laboratory apparatus commonly used for performing polymerase chain reaction (PCR). The device has a thermal block with holes where tubes with the PCR reaction mixtures can be inserted. The cycler then raises and lowers the temperature of the block in discrete, pre-programmed steps.

(adapted from http://serc.carleton.edu/microbelife/research_methods/genomics/pcr.html)";
    String instruments_1_instrument_name "PCR Thermal Cycler";
    String instruments_1_instrument_nid "471582";
    String keywords "bco, bco-dmo, bio, biological, BioProject, chemical, data, dataset, description, dmo, erddap, link, management, ncbi, NCBI_link, num, num_sequences, oceanography, office, preliminary, project, sample, sample_description, sequences, study, year";
    String license "https://www.bco-dmo.org/dataset/739077/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/739077";
    String param_mapping "{'739077': {}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/739077/parameters";
    String people_0_affiliation "University of Georgia";
    String people_0_affiliation_acronym "UGA";
    String people_0_person_name "Erin K. Lipp";
    String people_0_person_nid "553935";
    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 "Elizabeth Ottesen";
    String people_1_person_nid "553937";
    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 "Nancy Copley";
    String people_2_person_nid "50396";
    String people_2_role "BCO-DMO Data Manager";
    String people_2_role_type "related";
    String project "Vibrio-dust deposition";
    String projects_0_acronym "Vibrio-dust deposition";
    String projects_0_description 
"Description from NSF award abstract:
Dust and mineral aerosols are a significant source of micro and macronutrients to oligotrophic ocean surface waters. Evidence is growing that heterotrophic microbes may play key roles in processing deposited minerals and nutrients. Yet it is not known which components of dust stimulate the heterotrophic bacteria, which cellular mechanisms are responsible for the utilization of those components and how the activity of these bacteria affect the availability and utilization of dust-derived minerals and nutrients by marine autotrophs. Knowledge of these factors is key to understanding how dust deposition impacts carbon cycles and for predicting the response of tropical oceans to future changes in the frequency and intensity of dust deposition events. The objective of this project is to examine the specific effects of aeolian dust on heterotrophic microbes in a tropical marine system under controlled conditions. The central hypothesis is that in oligotrophic tropical systems numerically minor opportunistic bacteria are the first responders to influx of dust constituents and respond primarily by rapidly accessing soluble trace metals and limiting nutrients that are deposited with Saharan dust. The project will focus on two specific aims: 1) Quantify changes in community structure, composition and transcriptional activity among marine microbial populations upon exposure to dust, and 2) Identify key components in Saharan dust aerosols that stimulate or repress growth and/or activity in Vibrio, a model opportunistic marine heterotrophic group. The study will use a series of controlled experiments designed to identify and quantify heterotrophic microbial response to dust deposition events using both natural communities and model bacteria (Vibrio) through metagenomics, transcriptomics and atmospheric and marine biogeochemical techniques. This innovative approach will identify the most critical (reactive) components leached from dust aerosols on the microbial community as well as elucidate potential mechanisms of response.
There is great interest in the biological response to dust aerosols given its potentially large influence on biogeochemical cycling, but there has been relatively little work that has addressed the mechanisms of response (especially among the heterotrophic microbial fraction) or identified the relative importance of specific constituents of dust aerosols. A detailed framework for microbial response (focusing on opportunistic heterotrophs) will facilitate efforts to link autotrophic and heterotrophic processing. This contribution is significant because it will provide one of the first end-to-end (chemistry to physiology to ecology) mechanistic pathways for marine biological response to desert dust aerosols.";
    String projects_0_end_date "2017-03";
    String projects_0_geolocation "Florida Keys, FL, USA";
    String projects_0_name "Vibrio as a model microbe for opportunistic heterotrophic response to Saharan dust deposition events in marine waters";
    String projects_0_project_nid "553933";
    String projects_0_start_date "2014-04";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Accession numbers for raw sequences associated with field collections & microcosms, 2015 and 2016";
    String title "Accession numbers for raw sequences associated with field collections & microcosms, 2015 and 2016";
    String version "1";
    String xml_source "osprey2erddap.update_xml() v1.5";


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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