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Dataset Title:  [Ross Sea metaproteome peptide spectral counts] - Ross Sea metaproteome
peptide spectral counts searched against Phaeocystis strain transcriptome from
net tows during RVIB Nathaniel B. Palmer cruise NBP0601 in December of
2015 (Controls of Ross Sea Algal Community Structure)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_768259_v1)
Range: longitude = 170.76 to 170.76°E, depth = 5.0 to 5.0m, time = 2005-12-29T11:58:00Z to 2005-12-29T11:58:00Z
Information:  Summary ? | License ? | 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_id {
    String long_name "Sample_id";
    String units "unitless";
  }
  cruise_id {
    String long_name "Cruise_id";
    String units "unitless";
  }
  station_id {
    Int32 actual_range 137, 137;
    String long_name "Station_id";
    String units "unitless";
  }
  latitude_dd {
    Float32 actual_range -76.82, -76.82;
    String long_name "Latitude_dd";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 actual_range 170.76, 170.76;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude_dd";
    String standard_name "longitude";
    String units "degrees_east";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Int32 actual_range 5, 5;
    String axis "Z";
    String ioos_category "Location";
    String long_name "Depth_m";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  date_local {
    String long_name "Date_local";
    String units "unitless";
  }
  time_local {
    String long_name "Time_local";
    String units "unitless";
  }
  minimum_filter_size_microns {
    Int32 actual_range 20, 20;
    String long_name "Minimum_filter_size_microns";
    String units "microns (um)";
  }
  maximum_filter_size_microns {
    String long_name "Maximum_filter_size_microns";
    String units "microns (um)";
  }
  peptide_sequence {
    String long_name "Peptide_sequence";
    String units "unitless";
  }
  peptide_start_index {
    Int32 actual_range 0, 1458;
    String long_name "Peptide_start_index";
    String units "unitless";
  }
  peptide_stop_index {
    Int32 actual_range 0, 1474;
    String long_name "Peptide_stop_index";
    String units "unitless";
  }
  protein_molecular_weight_kDa {
    Float32 actual_range 0.0, 163516.0;
    String long_name "Protein_molecular_weight_kda";
    String units "kilo-Daltons (kDa)";
  }
  protein_id {
    String long_name "Protein_id";
    String units "unitless";
  }
  spectral_count_sum {
    Int32 actual_range 0, 66;
    String long_name "Spectral_count_sum";
    String units "unitless";
  }
  other_protein_ids {
    String long_name "Other_protein_ids";
    String units "unitless";
  }
  best_protein_id_probability {
    Float32 actual_range 0.945, 0.997;
    String long_name "Best_protein_id_probability";
    String units "unitless";
  }
  best_sequest_DCn_score {
    Float32 actual_range 0.2, 0.96;
    String long_name "Best_sequest_dcn_score";
    String units "unitless";
  }
  best_sequest_Xcorr_score {
    Float32 actual_range 2.5, 8.61;
    String long_name "Best_sequest_xcorr_score";
    String units "unitless";
  }
  plus2H_spectra_count {
    Int32 actual_range 0, 47;
    String long_name "Plus2h_spectra_count";
    String units "unitless";
  }
  plus3H_spectra_count {
    Int32 actual_range 0, 48;
    String long_name "Plus3h_spectra_count";
    String units "unitless";
  }
  plus4H_spectra_count {
    Int32 actual_range 0, 17;
    String long_name "Plus4h_spectra_count";
    String units "unitless";
  }
  median_retention_time {
    String long_name "Median_retention_time";
    String units "unitless";
  }
  total_precursor_intensity {
    String long_name "Total_precursor_intensity";
    String units "unitless";
  }
  TIC {
    String long_name "Tic";
    String units "unitless";
  }
  absolute_units_fmol_L {
    String long_name "Absolute_units_fmol_l";
    String units "femtomoles per liter (fmol/L)";
  }
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.13585748e+9, 1.13585748e+9;
    String axis "T";
    String ioos_category "Time";
    String long_name "Iso_datetime_utc";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
 }
  NC_GLOBAL {
    String cdm_data_type "Other";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_email "info@bco-dmo.org";
    String creator_name "BCO-DMO";
    String creator_url "https://www.bco-dmo.org/";
    String doi "10.26008/1912/bco-dmo.768259.2";
    Float64 Easternmost_Easting 170.76;
    Float64 geospatial_lon_max 170.76;
    Float64 geospatial_lon_min 170.76;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 5.0;
    Float64 geospatial_vertical_min 5.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2024-11-10T21:37:48Z (local files)
2024-11-10T21:37:48Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_768259_v1.das";
    String infoUrl "https://www.bco-dmo.org/dataset/768259";
    String institution "BCO-DMO";
    String license 
"The data may be used and redistributed for free but is not intended
for legal use, since it may contain inaccuracies. Neither the data
Contributor, ERD, NOAA, nor the United States Government, nor any
of their employees or contractors, makes any warranty, express or
implied, including warranties of merchantability and fitness for a
particular purpose, or assumes any legal liability for the accuracy,
completeness, or usefulness, of this information.";
    String sourceUrl "(local files)";
    String summary "A net tow metaproteome of a Phaeocystis antarctica bloom in the Ross Sea, mapped here to Phaeocystis metatranscriptomes analyzed by 2D LCMS, in units of peptide spectral counts.";
    String time_coverage_end "2005-12-29T11:58:00Z";
    String time_coverage_start "2005-12-29T11:58:00Z";
    String title "[Ross Sea metaproteome peptide spectral counts] - Ross Sea metaproteome peptide spectral counts searched against Phaeocystis strain transcriptome from net tows during RVIB Nathaniel B. Palmer cruise NBP0601 in December of 2015 (Controls of Ross Sea Algal Community Structure)";
    Float64 Westernmost_Easting 170.76;
  }
}

 

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
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/datasetID.fileType{?query}
For example,
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/pmelTaoDySst.htmlTable?longitude,latitude,time,station,wmo_platform_code,T_25&time>=2015-05-23T12:00:00Z&time<=2015-05-31T12:00:00Z
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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