Dataset: Quantifying cell densities and biovolumes of phytoplankton communities and functional groups using scanning flow cytometry, machine learning and unsupervised clustering
- 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
Files
Script 1. Training biovolume estimation.zip
Files
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