Fast and interpretable consensus clustering via minipatch learning

Luqin Gan; Genevera I. Allen

doi:10.1371/journal.pcbi.1010577

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Open Access

Peer-reviewed

Research Article

Fast and interpretable consensus clustering via minipatch learning

Luqin Gan ,

Roles Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: luain.gan@rice.edu

Affiliation Department of Statistics, Rice University, Houston, Texas, United States of America

https://orcid.org/0000-0002-0449-5376

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Genevera I. Allen

Roles Conceptualization, Funding acquisition, Project administration, Supervision, Writing – original draft, Writing – review & editing

Affiliations Departments of Electrical and Computer Engineering, Statistics, and Computer Science, Rice University, Houston, Texas, United States of America, Duncan Neurological Research Institute, Baylor College of Medicine, Houston, Texas, United States of America
⨯

Fast and interpretable consensus clustering via minipatch learning

Luqin Gan,
Genevera I. Allen

Published: October 3, 2022
https://doi.org/10.1371/journal.pcbi.1010577

About the Authors

Luqin Gan

Roles Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: luain.gan@rice.edu

Affiliation Department of Statistics, Rice University, Houston, Texas, United States of America

https://orcid.org/0000-0002-0449-5376

Genevera I. Allen

Roles Conceptualization, Funding acquisition, Project administration, Supervision, Writing – original draft, Writing – review & editing

Affiliations Departments of Electrical and Computer Engineering, Statistics, and Computer Science, Rice University, Houston, Texas, United States of America, Duncan Neurological Research Institute, Baylor College of Medicine, Houston, Texas, United States of America

Competing Interests

The authors have declared that no competing interests exist.

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Consensus clustering
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Bioinformatics
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Gene expression
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Clustering algorithms
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Hierarchical clustering
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Gene ontologies
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Embryos
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Covariance
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