Published September 28, 2017 | Version v1
Dataset Open

Dataset: Quantifying cell densities and biovolumes of phytoplankton communities and functional groups using scanning flow cytometry, machine learning and unsupervised clustering

Authors/Creators

  • 1. Centre for Ocean Life, Technical University of Denmark, Kemitorvet, Building 202, 2800 Kgs. Lyngby, Denmark
  • 2. Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Zürcherstrasse 111, 8903 Birmensdorf
  • 3. Dept. of Aquatic Ecology, Eawag: Swiss Federal Institute of Aquatic Science and Technology, Überlandstrasse 133, 8600 Dübendorf, Switzerland

Description

This dataset contains all relevant data for the manuscript (in submission) "Quantifying cell densities and biovolumes of phytoplankton communities and functional groups using scanning flow cytometry, machine learning and unsupervised clustering".

Code written to analyse this dataset (which may be adapted for other flow cytometry datasets) is found at https://zenodo.org/record/999747

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Naming convention for raw flow cytometry data files (located in /Script 3. Generating raw data subset/input/):

[Allparameters] _ [Year] - [Month] - [Date]  [Hour] [u] [Minute] _ [Depth]

e.g: Allparameters_2014-07-31 08u08_1.0m

The date, time and depth indicate the location and time at which the measurement was taken.

Notes

We are presently using this dataset for multiple publications that are in preparation. To avoid duplicated efforts, we request that you contact the authors if you are interested in pursuing a research project with this data. Contact information: Mridul K. Thomas - mrit {at} dtu {dot} dk Francesco Pomati - francesco {dot} pomati {at} eawag {dot} ch

Files

Script 1. Training biovolume estimation.zip

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