Sparse factor model for co-expression networks with an application using prior biological knowledge

DOI10.1515/sagmb-2015-0002zbMath1343.92184OpenAlexW2387609470WikidataQ38447540 ScholiaQ38447540MaRDI QIDQ306641

David Causeur, Magalie Houée-Bigot, Yuna Blum

Publication date: 1 September 2016

Published in: Statistical Applications in Genetics and Molecular Biology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1515/sagmb-2015-0002

zbMATH Keywords

sparsityfactor modelregularized estimationhigh dimensiongene ontologyrelevance network

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) General biostatistics (92B15) Genetics and epigenetics (92D10) Systems biology, networks (92C42) Software, source code, etc. for problems pertaining to information and communication theory (94-04)

Uses Software

• WGCNA
• glasso
• glmnet
• FAMT
• leapp
• dynamicTreeCut
• PMA

Cites Work

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• Note on “Comparison of Model Selection for Regression” by Vladimir Cherkassky and Yunqian Ma
• A Survey of Statistical Network Models
• High-Dimensional Sparse Factor Modeling: Applications in Gene Expression Genomics
• A General Framework for Weighted Gene Co-Expression Network Analysis