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Dataset Title:  RNA sequence accession numbers for coral colonies that displayed a strong
bleaching phenotype at Ofu Island, American Samoa between 2015 and 2016.
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_762511)
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Data Access Form | Files
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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 {
  sample {
    String bcodmo_name "sample";
    String description "Sample identifier";
    String long_name "Sample";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  colony {
    String bcodmo_name "sample";
    String description "Colony identifier";
    String long_name "Colony";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  species {
    String bcodmo_name "species";
    String description "Coral species";
    String long_name "Species";
    String units "uniless";
  date {
    String bcodmo_name "unknown";
    String description "Month and year of sampling in format yyyy_mm";
    String long_name "Date";
    String units "unitless";
  year {
    Int16 _FillValue 32767;
    Int16 actual_range 2015, 2016;
    String bcodmo_name "year";
    String description "Year of sampleing";
    String long_name "Year";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/YEARXXXX/";
    String units "unitless";
  month {
    String bcodmo_name "month";
    String description "Month of sampling";
    String long_name "Month";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/MNTHXXXX/";
    String units "unitless";
  bleaching_status {
    Byte _FillValue 127;
    Byte actual_range 0, 100;
    String bcodmo_name "sample_descrip";
    String description "Bleaching status";
    String long_name "Bleaching Status";
    String units "percent";
  Accession {
    String bcodmo_name "accession number";
    String description "Genetic accession number at NCBI";
    String long_name "Accession";
    String units "unitless";
  Accession_link {
    String bcodmo_name "external_link";
    String description "Link to genetic accession at NCBI";
    String long_name "Accession Link";
    String units "unitless";
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"Colonies that displayed a strong bleaching phenotype in April 2015 were
selected for transcriptome-wide gene expression analyses. These colonies were
subsequently sampled in August 2015, December 2015 and April 2016. For these
36 field-collected tissue samples (five colonies of A. gemmifera and four
colonies of A. hyacinthus across four sample dates), total RNA was extracted
Qiagens RNAeasy Plus Kit. In total 36 cDNA libraries were generated using the
Illumina TruSeq RNA Library Prep Kit v2 with Protoscript II Reverse
Transcriptase. We carried out multiplexed Illumina sequencing at the
University of Utah Microarray and Genomic Analysis Core Facility. Fastq files
were mapped to a reference transcriptome (Barshis et al., 2013) using HISAT2
(Langmead & Salzberg, 2012) with a minimum mapping quality of 10. We used
SAMtools (Li et al., 2009) to generate counts for each contig in our reference
transcriptome. Counts matrices were normalized in DESeq2.0 (Love, Huber, &
Anders, 2014).
Approximate coordinates for this dataset are \"Pool 400\", back reef lagoon,
Ofu, American Samoa (-14.17990, -169.65448)";
    String awards_0_award_nid "647913";
    String awards_0_award_number "OCE-1547921";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1547921";
    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 
"Sequence accessions: Hidden resilience to recurrent bleaching 
  PI: Stephen Palumbi 
  Data Version 1: 2019-03-18";
    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 "2019-03-18T18:45:27Z";
    String date_modified "2019-04-26T21:24:46Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.762511.2";
    String history 
"2022-08-12T23:40:42Z (local files)
2022-08-12T23:40:42Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_762511.das";
    String infoUrl "https://www.bco-dmo.org/dataset/762511";
    String institution "BCO-DMO";
    String instruments_0_acronym "Automated Sequencer";
    String instruments_0_dataset_instrument_nid "762537";
    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 2500";
    String keywords "accession, Accession_link, bco, bco-dmo, biological, bleaching, bleaching_status, chemical, colony, data, dataset, date, dmo, erddap, link, management, month, oceanography, office, preliminary, sample, species, status, year";
    String license "https://www.bco-dmo.org/dataset/762511/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/762511";
    String param_mapping "{'762511': {}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/762511/parameters";
    String people_0_affiliation "Stanford University";
    String people_0_person_name "Stephen R. Palumbi";
    String people_0_person_nid "51368";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of Western Australia";
    String people_1_person_name "Luke Thomas";
    String people_1_person_nid "762507";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "Stanford University";
    String people_2_person_name "Stephen R. Palumbi";
    String people_2_person_nid "51368";
    String people_2_role "Contact";
    String people_2_role_type "related";
    String people_3_affiliation "Woods Hole Oceanographic Institution";
    String people_3_affiliation_acronym "WHOI BCO-DMO";
    String people_3_person_name "Amber York";
    String people_3_person_nid "643627";
    String people_3_role "Data Manager";
    String people_3_role_type "related";
    String project "Bleaching American Samoa";
    String projects_0_acronym "Bleaching American Samoa";
    String projects_0_description 
"Description from NSF award abstract:
The strongest coral bleaching event in nearly 20 years began in American Samoa in January 2015. Coral bleaching occurs when ocean water temperatures exceed a coral's normal heat tolerance. But bleaching events usually show an unexplained pattern - colonies next to one another can show very different levels of bleaching - from pure white to the normal tan color of a healthy coral. The investigators have observed this pattern among 280 corals on reefs in American Samoa that have been studied for years. This system will be used to test four major hypotheses about what causes some corals to bleach and some not: differences in 1) species, 2) the temperature the corals experienced, 3) the symbiont they harbor, and 4) the genotype of the coral host. In addition, the investigators will return to American Samoa at regular intervals to measure the rate of recovery of each coral colony and conduct the same tests as above for recovery rate. The stark-white reefscapes left behind by bleaching events are one of the most common signals of increased ocean warming. This work will take advantage of years of prior study and the advent of a coral bleaching event to understand the rules for survival on reefs.
The reefs of American Samoa began showing a major bleaching event starting in January 2015, including 62 corals that have been intensively studied for coral thermal resistance, field temperatures, and symbiont type. In April 2015 the investigators monitored bleaching status of these and additional corals, totaling 280 corals from four species, and uncovered marked variation in bleaching extent within and between species and within and between reef regions. The team will test the relative importance of microclimate to bleaching state by examining records of approximately 50 temperature loggers in place since before the bleaching event. They will test the influence of symbiont type and host gene expression profiles by examining samples of 60 colonies taken at four time points after bleaching. The investigators will also examine the full suite of 280 corals for genetic variation to estimate the relationship between bleaching state, recovery rate and genetic polymorphism. These data will be used to test micro-climate, symbiont, and coral genetics as determinants of bleaching and bleaching recovery. Because the investigators have samples from these 280 colonies before bleaching mortality, this study will provide the first estimate for the evolutionary impact of a bleaching event on coral populations.";
    String projects_0_end_date "2017-06";
    String projects_0_geolocation "American Samoa";
    String projects_0_name "Ecological, evolutionary and physiological responses of corals to a mass bleaching event in American Samoa";
    String projects_0_project_nid "647914";
    String projects_0_start_date "2015-07";
    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 summary "RNA sequence accession numbers for coral colonies that displayed a strong bleaching phenotype at Ofu Island, American Samoa between 2015 and 2016. This dataset includes accession numbers for 36 RNAseq libraries housed at The National Center for Biotechnology Information (NCBI).";
    String title "RNA sequence accession numbers for coral colonies that displayed a strong bleaching phenotype at Ofu Island, American Samoa between 2015 and 2016.";
    String version "2";
    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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