Architecture and implementation of ulrb algorithm in R, source data
Description
This dataset makes available the source data used for all analyses made in the original research article entitled "Architecture and implementation of ulrb algorithm in R", for the journal Ecological Informatics. Short description of files: nice_ASVs.csv - ASV abundance table in long format; nice_otu_long - OTU abundance table in long format; nice_otu_wide - OTU abundance table in wide format. All files correspond to samples collected from seawater of the Arctic Ocean, during the Norwegian Young Sea Ice Expedition, using V4V5 16S rRNA gene amplicon sequencing. To use this dataset, please cite: - Pascoal, F. et al. (2025) “Definition of the microbial rare biosphere through unsupervised machine learning,” Communications Biology, 8(1), p. 544. Available at: https://doi.org/10.1038/s42003-025-07912-4. - Pascoal, F. et al. (2022) “Exploration of the Types of Rarity in the Arctic Ocean from the Perspective of Multiple Methodologies,” Microbial Ecology, 84(1), pp. 59–72. Available at: https://doi.org/10.1007/s00248-021-01821-9. - de Sousa, A.G.G. et al. (2019) “Diversity and Composition of Pelagic Prokaryotic and Protist Communities in a Thin Arctic Sea-Ice Regime,” Microbial Ecology, 78(2), pp. 388–408. Available at: https://doi.org/10.1007/s00248-018-01314-2. - Granskog, M.A. et al. (2018) “Atmosphere-Ice-Ocean-Ecosystem Processes in a Thinner Arctic Sea Ice Regime: The Norwegian Young Sea ICE (N-ICE2015) Expedition,” Journal of Geophysical Research: Oceans, 123(3), pp. 1586–1594. Available at: https://doi.org/10.1002/2017JC013328.
Files
Institutions
- University of Ottawa School of Electrical Engineering and Computer Science
- Centro Interdisciplinar de Investigacao Marinha e Ambiental da Madeira
- Universidade de Lisboa Instituto Superior Tecnico
- Universidade do Porto Faculdade de Ciencias