Utilizing stability criteria in choosing feature selection methods yields reproducible results in microbiome data-Reference-Cited by-同舟云学术

Utilizing stability criteria in choosing feature selection methods yields reproducible results in microbiome data

Published:2021-05-19 Issue: Volume: Page:
ISSN:0006-341X
Container-title:Biometrics
language:en
Short-container-title:Biometrics

Author:

Jiang Lingjing¹^ORCID,Haiminen Niina²^ORCID,Carrieri Anna‐Paola³^ORCID,Huang Shi⁴⁵^ORCID,Vázquez‐Baeza Yoshiki⁴⁵^ORCID,Parida Laxmi²^ORCID,Kim Ho‐Cheol⁶^ORCID,Swafford Austin D.⁴^ORCID,Knight Rob⁴⁵⁷⁸^ORCID,Natarajan Loki¹^ORCID

Affiliation:

1. Division of Biostatistics University of California San Diego La Jolla California USA

2. IBM T. J. Watson Research Center Yorktown Heights New York USA

3. IBM Research The Hartree Center Warrington UK

4. Center for Microbiome Innovation Jacobs School of Engineering UC San Diego La Jolla California USA

5. Department of Pediatrics University of California San Diego La Jolla California USA

6. Scalable Knowledge Intelligence IBM Research‐Almaden San Jose California USA

7. Department of Computer Science and Engineering University of California San Diego La Jolla California USA

8. Department of Bioengineering University of California San Diego La Jolla California USA

Funder

National Institute of Diabetes and Digestive and Kidney Diseases

Publisher

Wiley

Subject

Applied Mathematics,General Agricultural and Biological Sciences,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,Statistics and Probability

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/biom.13481

Reference41 articles.

1. The Statistical Analysis of Compositional Data

2. Permutation importance: a corrected feature importance measure

3. 1,500 scientists lift the lid on reproducibility

4. Microbiome Data Accurately Predicts the Postmortem Interval Using Random Forest Regression Models

5. Stability and aggregation of ranked gene lists

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