Corpus ID: 219176565

CLARITY -- Comparing heterogeneous data using dissimiLARITY

@article{Lawson2020CLARITYC,
  title={CLARITY -- Comparing heterogeneous data using dissimiLARITY},
  author={Daniel John Lawson and Vinesh Solanki and Igor Yanovich and Johannes Dellert and Damian J. Ruck and Phillip Endicott},
  journal={arXiv: Methodology},
  year={2020}
}
Integrating datasets from different disciplines is hard because the data are often qualitatively different in meaning, scale, and reliability. When two datasets describe the same entities, many scientific questions can be phrased around whether the similarities between entities are conserved. Our method, CLARITY, quantifies consistency across datasets, identifies where inconsistencies arise, and aids in their interpretation. We explore three diverse comparisons: Gene Methylation vs Gene… Expand

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