Testing for dependence on tree structures

Behr M, Ansari MA, Munk A, Holmes C (2020)

Publication Type: Journal article

Publication year: 2020

Journal

Proceedings of the National Academy of Sciences of the United States of America National Academy of Sciences

Book Volume: 117

Pages Range: 9787-9792

Journal Issue: 18

DOI: 10.1073/pnas.1912957117

Abstract

Tree structures, showing hierarchical relationships and the latent structures between samples, are ubiquitous in genomic and biomedical sciences. A common question in many studies is whether there is an association between a response variable measured on each sample and the latent group structure represented by some given tree. Currently, this is addressed on an ad hoc basis, usually requiring the user to decide on an appropriate number of clusters to prune out of the tree to be tested against the response variable. Here, we present a statistical method with statistical guarantees that tests for association between the response variable and a fixed tree structure across all levels of the tree hierarchy with high power while accounting for the overall false positive error rate. This enhances the robustness and reproducibility of such findings.

Involved external institutions

University of California, Berkeley US United States (USA) (US) University of Oxford GB United Kingdom (GB) Georg-August-Universität Göttingen DE Germany (DE)

How to cite

APA:

Behr, M., Ansari, M.A., Munk, A., & Holmes, C. (2020). Testing for dependence on tree structures. Proceedings of the National Academy of Sciences of the United States of America, 117(18), 9787-9792. https://dx.doi.org/10.1073/pnas.1912957117

MLA:

Behr, Merle, et al. "Testing for dependence on tree structures." Proceedings of the National Academy of Sciences of the United States of America 117.18 (2020): 9787-9792.

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