Accessing BCO-DMO data
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Dataset Title:  Transcriptome data for bacteria collected eight hours after individual
inoculation into a diatom Thalassiosira psuedonana culture
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_818765)
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Subset | Files
Variable ?   Optional
Constraint #1 ?
Constraint #2 ?
   Minimum ?
   or a List of Values ?
   Maximum ?
 Sample_Name (unitless) ?          "TMC1"    "TME2"
 NCBI_Bioproject_Accession (unitless) ?      
   - +  ?
 BioSample (unitless) ?          "SAMN08987934"    "SAMN08987937"
 Description (unitless) ?          "Bacteria co-cultur..."    "Bacteria glucose c..."
 replicate (unitless) ?          1    2
 NCBI_Genome_Accession (unitless) ?          "ASM1196v2"    "ASM15857v1"
 taxon_microbe (unitless) ?          "Dokdonia sp. MED134"    "Thalassiosira pseu..."
Server-side Functions ?
 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.Hover here to see a list of options. Click on an option to select it.")

File type: (more info)

(Documentation / Bypass this form ? )
(Please be patient. It may take a while to get the data.)


The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  Sample_Name {
    String bcodmo_name "sample";
    String description "sample identifier";
    String long_name "Sample Name";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  NCBI_Bioproject_Accession {
    String bcodmo_name "accession number";
    String description "NCBI Bioproject accession number";
    String long_name "NCBI Bioproject Accession";
    String units "unitless";
  BioSample {
    String bcodmo_name "accession number";
    String description "NCBI Biosample accession number";
    String long_name "Bio Sample";
    String units "unitless";
  Description {
    String bcodmo_name "sample_descrip";
    String description "Description of sample";
    String long_name "Description";
    String units "unitless";
  replicate {
    Byte _FillValue 127;
    Byte actual_range 1, 2;
    String bcodmo_name "replicate";
    String description "Replicate number";
    String long_name "Replicate";
    String units "unitless";
  NCBI_Genome_Accession {
    String bcodmo_name "accession number";
    String description "NCBI Genome accession number";
    String long_name "NCBI Genome Accession";
    String units "unitless";
  taxon_microbe {
    String bcodmo_name "taxon";
    String description "Microbial identification";
    String long_name "Taxon Microbe";
    String units "unitless";
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"Thalassiosira pseudonana were removed from the co-cultures by pre-filtration
through 2.0 \\u00b5m pore-size filters, and bacteria were collected on 0.2
\\u00b5m pore-size filters. Filters were incubated in SDS (0.6% final
concentration) and proteinase K (120 ng \\u03bcl \\u20131 final concentration).
RNA was extracted from duplicates of each treatment by adding an equal volume
of acid phenol:chloroform:isoamyl-alcohol, followed by shaking,
centrifugation, and collection of the supernatant. A second extraction was
carried out by the addition of an equal volume of chloroform:isoamyl-alcohol.
RNA was recovered from the supernatant, treated to remove rRNA, and sequenced.
Each sequence library is from four independent bacterial samples that were
pooled for sequencing. The data are assigned to one of the four samples post-
sequencing by mapping to the genomes of each of the four bacteria. The data
table provides the accession numbers of the bacterial genomes to be used for
mapping in the final column.";
    String awards_0_award_nid "765520";
    String awards_0_award_number "IOS-1656311";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1656311";
    String awards_0_funder_name "NSF Division of Integrative Organismal Systems";
    String awards_0_funding_acronym "NSF IOS";
    String awards_0_funding_source_nid "626136";
    String awards_0_program_manager "Mamta Rawat";
    String awards_0_program_manager_nid "765519";
    String cdm_data_type "Other";
    String comment 
"Diatom Matrix RNAseq 
     NCBI accessions for transcriptome data for bacteria collected 8 hrs after individual inoculation into a diatom Thalassiosira psuedonana culture. 
   PI: M. A. Moran (UGA) 
   version date: 2020-07-16";
    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 "2020-07-16T14:58:37Z";
    String date_modified "2020-07-20T20:17:45Z";
    String defaultDataQuery "&time<now";
    String doi "10.26008/1912/bco-dmo.818765.1";
    String history 
"2021-10-21T20:56:38Z (local files)
2021-10-21T20:56:38Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_818765.html";
    String infoUrl "https://www.bco-dmo.org/dataset/818765";
    String institution "BCO-DMO";
    String instruments_0_acronym "Automated Sequencer";
    String instruments_0_dataset_instrument_nid "818797";
    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 "HiSeq Illumina 2500";
    String keywords "accession, bco, bco-dmo, bio, biological, bioproject, BioSample, chemical, data, dataset, description, dmo, erddap, genome, management, microbe, name, ncbi, NCBI_Bioproject_Accession, NCBI_Genome_Accession, oceanography, office, preliminary, replicate, sample, Sample_Name, taxon, taxon_microbe";
    String license "https://www.bco-dmo.org/dataset/818765/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/818765";
    String param_mapping "{'818765': {}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/818765/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 "Woods Hole Oceanographic Institution";
    String people_1_affiliation_acronym "WHOI BCO-DMO";
    String people_1_person_name "Nancy Copley";
    String people_1_person_nid "50396";
    String people_1_role "BCO-DMO Data Manager";
    String people_1_role_type "related";
    String project "Metabolic Currencies";
    String projects_0_acronym "Metabolic Currencies";
    String projects_0_description 
"NSF Award Abstract:
The roles of microbes in cycling carbon and nutrients in the ocean - the largest biological system on Earth - were initially described about 40 years ago. Now, it is known that half of Earth's primary production is carried out by marine phytoplankton, and half of that is recycled within weeks by marine bacteria. This proposal is a collaboration between microbiologists and chemists to identify the specific compounds that pass between phytoplankton and bacteria in surface ocean waters. Identifying the key chemicals of the ocean's microbial food web will provide insights into how the marine carbon cycle is regulated, generate data to improve ocean carbon models, and train new scientists at the interface of microbiology and chemistry. Hands-on learning opportunities in microbial ecology will be provided for high school students, both in the classroom and in marine ecosystems of the Georgia coast.
Phytoplankton metabolites that sustain the flow of carbon between microbial autotrophs and heterotrophs in the surface ocean carbon cycle will be identified in this project. A matrix of model systems consisting of bacteria-phytoplankton co-cultures will be used as biological assays for key metabolites based on expression patterns of bacterial transporter genes. The chemical identity of candidate metabolites and evaluation of their potential ecological role will be carried out by exometabolomic analysis of co-cultures with bacterial transporter mutants. Both advanced mass spectrometry and NMR will be used for metabolomics analysis, taking advantage of the sensitivity and compound identification strengths of each. The distribution of candidate metabolites in the ocean microbiome and other microbial systems will be characterized by mining environmental sequence datasets for orthologous transporter genes. This project represents a novel approach to identifying metabolites important in microbiome function, compounds often difficult to address with standard chemical approaches because of their low concentrations and high biological demand.";
    String projects_0_end_date "2020-06";
    String projects_0_name "Metabolic Currencies of the Ocean Carbon Cycle";
    String projects_0_project_nid "765521";
    String projects_0_start_date "2017-07";
    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 subsetVariables "NCBI_Bioproject_Accession";
    String summary "Transcriptome data for bacteria Ruegeria pomeroyi DSS-3, Stenotrophomonas sp. SKA14, Polaribacter dokdonensis MED152, and Dokdonia MED134 collected eight hours after individual inoculation into a diatom Thalassiosira psuedonana culture. The sequence data description for PRHNA448168 is at https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA448168.";
    String title "Transcriptome data for bacteria collected eight hours after individual inoculation into a diatom Thalassiosira psuedonana culture";
    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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