Accessing BCO-DMO data
log in    
Brought to you by BCO-DMO    

ERDDAP > tabledap > Data Access Form ?

Dataset Title:  DYEatom Metatranscriptome metadata from RV/Point Sur cruise PS1312 in the
Monterey Bay area, June-July 2013
Subscribe RSS
Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_768550)
Information:  Summary ? | License ? | Metadata | Background (external link) | Subset | Files | Make a graph
Variable ?   Optional
Constraint #1 ?
Constraint #2 ?
   Minimum ?
   or a List of Values ?
   Maximum ?
 BioProject_type (unitless) ?      
   - +  ?
 BioProject_id (unitless) ?      
   - +  ?
 BioSample (unitless) ?          "SAMN11258802"    "SAMN11263639"
 Sample_name (unitless) ?          "DYEatom_16S_10_1"    "DYEatom_MetaT_9_55"
 SRA_id (unitless) ?          "SRS4545423"    "SRS4545494"
 Package_type (unitless) ?      
   - +  ?
 version (unitless) ?      
   - +  ?
 Accession (unitless) ?          "SAMN11258802"    "SAMN11263639"
 ID (unitless) ?          11258802    11263639
 cruise_id (unitless) ?      
   - +  ?
 CTD_cast (unitless) ?          "CTD05"    "CTD35"
 latitude (degrees_north) ?          36.455    38.265
  < slider >
 longitude (degrees_east) ?          -123.969    -121.981
  < slider >
 Date_collection (unitless) ?          "2013-06-28"    "2013-07-05"
 station (unitless) ?          2    11
 depth (m) ?          1.6    55.5
  < slider >
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 {
  BioProject_type {
    String bcodmo_name "exp_type";
    String description "NCBI BioProject type";
    String long_name "Bio Project Type";
    String units "unitless";
  BioProject_id {
    String bcodmo_name "exp_id";
    String description "NCBI BioProject identifier";
    String long_name "Bio Project Id";
    String units "unitless";
  BioSample {
    String bcodmo_name "accession number";
    String description "NCBI BioSample identifier";
    String long_name "Bio Sample";
    String units "unitless";
  Sample_name {
    String bcodmo_name "sample";
    String description "NCBI Sample identifier";
    String long_name "Sample Name";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  SRA_id {
    String bcodmo_name "sample";
    String description "NCBI SRA identifier";
    String long_name "SRA Id";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  Package_type {
    String bcodmo_name "sample_type";
    String description "NCBI Package type";
    String long_name "Package Type";
    String units "unitless";
  version {
    Byte _FillValue 127;
    Byte actual_range 1, 1;
    String bcodmo_name "unknown";
    String description "NCBI version";
    String long_name "Version";
    String units "unitless";
  Accession {
    String bcodmo_name "accession number";
    String description "NCBI Accession";
    String long_name "Accession";
    String units "unitless";
  ID {
    Int32 _FillValue 2147483647;
    Int32 actual_range 11258802, 11263639;
    String bcodmo_name "accession number";
    String description "NCBI ID";
    String long_name "ID";
    String units "unitless";
  cruise_id {
    String bcodmo_name "cruise_id";
    String description "cruise identifier";
    String long_name "Cruise Id";
    String units "unitless";
  CTD_cast {
    String bcodmo_name "cast";
    String description "CTD cast number";
    String long_name "CTD Cast";
    String units "unitless";
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 36.455, 38.265;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "latitude; north is positive";
    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 -123.969, -121.981;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "longitude; east is positive";
    String ioos_category "Location";
    String long_name "Longitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LONX/";
    String source_name "Long";
    String standard_name "longitude";
    String units "degrees_east";
  Date_collection {
    String bcodmo_name "date";
    String description "date of collection; formatted as yyyy-mm-dd";
    String long_name "Date Collection";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String source_name "Date_collection";
    String time_precision "1970-01-01";
    String units "unitless";
  station {
    Byte _FillValue 127;
    Byte actual_range 2, 11;
    String bcodmo_name "station";
    String description "station number";
    String long_name "Station";
    String units "unitless";
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 1.6, 55.5;
    String axis "Z";
    String bcodmo_name "depth";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "depth of sample";
    String ioos_category "Location";
    String long_name "Depth";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/DEPH/";
    String positive "down";
    String standard_name "depth";
    String units "m";
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"Water was collected using Niskin bottles mounted on a CTD rosette. Biomass for
metatranscriptomic analysis was collected by filtration (after a 200 micron
pre-filtration) onto 47 mm, 1.2-micron pore size polycarbonate filters at <5
psi for no longer than 15 min to minimize degradation. Filters were flash
frozen in liquid nitrogen and stored at -80 degrees C. Upon analysis, filters
were thawed and RNA was extracted using TRIzol reagent according to the
manufacturer\\u2019s protocol (Life Technologies). Metatranscriptome libraries
were constructed using 500 ng of total RNA and a TruSeq RNA Sample Preparation
Kit (Illumina; San Diego, CA) following the Low-Throughput protocol. The mean
size of the final libraries was confirmed to be between 359-420 base pairs
(bp) using an Agilent Bioanalyzer 2100 (Santa Clara, CA). Libraries were
paired-end sequenced (2x150 bp) on the Illumina HiSeq platform. ORFs were
annotated via BLASTP alignment (e-value > 10-3) to a comprehensive protein
database, phyloDB, as well as screened for function de-novo by assigning
Pfams, TIGRfams and transmembrane tmHMMs with hmmer 3.0
([http://hmmer.org/](\\\\\"http://hmmer.org/\\\\\")). PhyloDB 1.076 consists of
24,509,327 peptides from 19,962 viral, 230 archaeal, 4,910 bacterial, and 894
eukaryotic taxa. It includes peptides at KEGG, GenBank, JGI, ENSEMBL, CAMERA,
and various other repositories, as well as from the 410 taxa of the Marine
Microbial Eukaryotic Transcriptome Sequencing Project. Taxonomic annotation of
ORFs was also conducted via BLASTP to phyloDB.
All cruise related data are available publicly at the Biological and Chemical
Oceanography Data Management Office under project number 550825 ([https://www
The metatranscriptomic data have been deposited in the NCBI sequence read
archive (BioProject accession no. PRJNA528986: BioSample accession nos.
SAMN11263616 - SAMN11263639 and SAMN11258802-SAMN11258825). Assembled contigs
used in this study can also be found at
Unassembled reads and rRNA data from this
 Assembled contigs: See Supplemental Files.";
    String awards_0_award_nid "558197";
    String awards_0_award_number "OCE-1333929";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1333929";
    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 
"DYEatom Metatranscriptome  
   from RV/Point Sur cruise PS1312, DYEatom cruise, June-July 2013 
   PI: K. Thamatrakoln (Rutgers) 
   version date: 2019-05-29";
    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 "2019-05-23T19:52:52Z";
    String date_modified "2019-07-31T16:26:40Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.768550.1";
    Float64 Easternmost_Easting -121.981;
    Float64 geospatial_lat_max 38.265;
    Float64 geospatial_lat_min 36.455;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -121.981;
    Float64 geospatial_lon_min -123.969;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 55.5;
    Float64 geospatial_vertical_min 1.6;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2021-12-05T02:38:22Z (local files)
2021-12-05T02:38:22Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_768550.html";
    String infoUrl "https://www.bco-dmo.org/dataset/768550";
    String institution "BCO-DMO";
    String instruments_0_acronym "Automated Sequencer";
    String instruments_0_dataset_instrument_nid "768559";
    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 HiSeq platform";
    String keywords "accession, bco, bco-dmo, bio, biological, BioProject_id, BioProject_type, BioSample, cast, chemical, collection, conductivity, cruise, cruise_id, ctd, CTD_cast, data, dataset, date, depth, depth_m, dmo, erddap, latitude, longitude, management, name, oceanography, office, package, Package_type, preliminary, project, sample, Sample_name, sonde, sra, SRA_id, station, temperature, time, type, version";
    String license "https://www.bco-dmo.org/dataset/768550/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/768550";
    Float64 Northernmost_Northing 38.265;
    String param_mapping "{'768550': {'Lat': 'flag - latitude', 'depth_m': 'flag - depth', 'Long': 'flag - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/768550/parameters";
    String people_0_affiliation "Rutgers University";
    String people_0_affiliation_acronym "Rutgers IMCS";
    String people_0_person_name "Kimberlee Thamatrakoln";
    String people_0_person_nid "558200";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "J. Craig Venter Institute";
    String people_1_affiliation_acronym "JCVI";
    String people_1_person_name "Andrew E Allen";
    String people_1_person_nid "51525";
    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 "Diatom Silicification";
    String projects_0_acronym "Diatom Silicification";
    String projects_0_description 
"Description from NSF award abstract:
Diatoms, unicellular, eukaryotic photoautotrophs, are among the most ecologically successful and functionally diverse organisms in the ocean. In addition to contributing one-fifth of total global primary productivity, diatoms are also the largest group of silicifying organisms in the ocean. Thus, diatoms form a critical link between the carbon and silicon (Si) cycles. The goal of this project is to understand the molecular regulation of silicification processes in natural diatom populations to better understand the processes controlling diatom productivity in the sea. Through culture studies and two research cruises, this research will couple classical measurements of silicon uptake and silica production with molecular and biochemical analyses of Silicification-Related Gene (SiRG) and protein expression. The proposed cruise track off the West Coast of the US will target gradients in Si and iron (Fe) concentrations with the following goals: 1) Characterize the expression pattern of SiRGs, 2) Correlate SiRG expression patterns to Si concentrations, silicon uptake kinetics, and silica production rates, 3) Develop a method to normalize uptake kinetics and silica production to SiRG expression levels as a more accurate measure of diatom activity and growth, 4) Characterize the diel periodicity of silica production and SiRG expression.
It is estimated that diatoms process 240 Teramoles of biogenic silica each year and that each molecule of silicon is cycled through a diatom 39 times before being exported to the deep ocean. Decades of oceanographic and field research have provided detailed insight into the dynamics of silicon uptake and silica production in natural populations, but a molecular understanding of the factors that influence silicification processes is required for further understanding the regulation of silicon and carbon fluxes in the ocean. Characterizing the genetic potential for silicification will provide new information on the factors that regulate the distribution of diatoms and influence in situ rates of silicon uptake and silica production. This research is expected to provide significant information about the molecular regulation of silicification in natural populations and the physiological basis of Si limitation in the sea.";
    String projects_0_end_date "2016-08";
    String projects_0_geolocation "Oregon/California Coastal Upwelling Zone, between 34-44N and 120-124W";
    String projects_0_name "Linking physiological and molecular aspects of diatom silicification in field populations";
    String projects_0_project_nid "558198";
    String projects_0_start_date "2013-09";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 36.455;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String subsetVariables "BioProject_type,BioProject_id,Package_type,version,cruise_id";
    String summary "Metadata for assembled contigs and ORFS from metatranscriptome analysis from CTD casts in the Monterey Bay area on RV/Point Sur cruise PS1312, June-July 2013. Assembled contigs files are also available; see Supplemental Files.";
    String title "DYEatom Metatranscriptome metadata from RV/Point Sur cruise PS1312 in the Monterey Bay area, June-July 2013";
    String version "1";
    Float64 Westernmost_Easting -123.969;
    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.

ERDDAP, Version 2.02
Disclaimers | Privacy Policy | Contact