Integrative analysis of transcriptomic and metabolomic data via sparse canonical correlation analysis with incorporation of biological information-Reference-Cited by-同舟云学术

Integrative analysis of transcriptomic and metabolomic data via sparse canonical correlation analysis with incorporation of biological information

Published:2017-05-08 Issue:1 Volume:74 Page:300-312
ISSN:0006-341X
Container-title:Biometrics
language:en
Short-container-title:Biom

Author:

Safo Sandra E.¹^ORCID,Li Shuzhao²,Long Qi³

Affiliation:

1. Department of Biostatistics and Bioinformatics; Emory University; Atlanta, Georgia U.S.A.

2. Department of Medicine, Division of Pulmonary, Allergy and Critical Care Medicine; Emory University; Atlanta, Georgia U.S.A.

3. Department of Biostatistics, Epidemiology and Informatics; University of Pennsylvania; Philadelphia U.S.A.

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

http://onlinelibrary.wiley.com/wol1/doi/10.1111/biom.12715/fullpdf

Reference25 articles.

1. Uric acid: Role in cardiovascular disease and effects of losartan;Alderman;Current Medical Research Opinion,2004

2. A direct estimation approach to sparse linear discriminant analysis;Cai;Journal of the American Statistical Association,2011

3. The Dantzig selector: Statistical estimation when p is much larger than n;Candes;The Annals of Statistics,2007

4. Comparison of penalty functions for sparse canonical correlation analysis;Chalise;Computational Statistics and Data Analysis,2012

5. Toppgene suite for gene list enrichment analysis and candidate gene prioritization;Chen;Nucleic Acids Research,2009

Cited by 20 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Knowledge-guided learning methods for integrative analysis of multi-omics data;Computational and Structural Biotechnology Journal;2024-12

2. DeepIDA-GRU: a deep learning pipeline for integrative discriminant analysis of cross-sectional and longitudinal multiview data with applications to inflammatory bowel disease classification;Briefings in Bioinformatics;2024-05-23

3. Single-cell biclustering for cell-specific transcriptomic perturbation detection in AD progression;Cell Reports Methods;2024-04

4. Interpretable deep learning methods for multiview learning;BMC Bioinformatics;2024-02-14

5. Identifying important gene signatures of BMI using network structure‐aided nonparametric quantile regression;Statistics in Medicine;2023-02-23