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Testing for dependence on tree structures.
Behr, Merle; Ansari, M Azim; Munk, Axel; Holmes, Chris.
Afiliação
  • Behr M; Department of Statistics, University of California, Berkeley, CA 94720.
  • Ansari MA; Department of Statistics, University of Oxford, Oxford OX1 3LB, United Kingdom.
  • Munk A; Wellcome Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, United Kingdom.
  • Holmes C; Institute for Mathematical Stochastics, University of Göttingen, Göttingen 37077, Germany.
Proc Natl Acad Sci U S A ; 117(18): 9787-9792, 2020 05 05.
Article em En | MEDLINE | ID: mdl-32321827
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article