Compositional transformations can reasonably introduce phenotype-associated values into sparse features
Gihawi et al. claim that finding that a transformation turned highly sparse (mostly zero) features into features that are associated with a phenotype is sufficient to conclude that there is information leakage and to invalidate an analysis. This claim has critical implications for both the debate regarding The Cancer Genome Atlas (TCGA) cancer microbiome analysis and for interpretation and evaluation of analyses in the microbiome field at large. We show by counterexamples and by reanalysis that such transformations can be valid.
Authors
- Tal Korem (ORCID: https://orcid.org/0000-0002-0609-0858)
- George I. Austin (ORCID: https://orcid.org/0000-0002-7834-4968)
Institutions
- Columbia University Irving Medical Center (US)
- Columbia University (US)
Publication Details
- Journal
- mSystems
- Published
- 2025-05-02
- DOI
- https://doi.org/10.1128/msystems.00021-25
- Citations
- 4
- Primary Topic
- Geochemistry and Geologic Mapping
- Type
- article
- Field-Weighted Citation Impact
- 9.92
Funders
- U.S. National Library of Medicine