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KG-SCCA specifications


Unique identifier OMICS_19426
Alternative name Knowledge-Guided Sparse Canonical Correlation Analysis
Software type Application/Script
Interface Command line interface
Restrictions to use None
Computer skills Advanced
Stability Stable
Maintained Yes


No version available


  • person_outline Li Shen <>

Publication for Knowledge-Guided Sparse Canonical Correlation Analysis

KG-SCCA citation


Structured sparse CCA for brain imaging genetics via graph OSCAR

PMCID: 5009827
PMID: 27585988
DOI: 10.1186/s12918-016-0312-1

[…] h used the ℓ1-norm of |ρij|(ui−sign(ρij)uj) to pull those positively correlated features together, and fused those negatively correlated features to the opposite direction. the knowledge-guided scca (kg-scca) [] was an extension of both ns-scca [, ] and s2cca []. it used ℓ2-norm of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usep […]

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KG-SCCA institution(s)
BioHealth, Indiana University School of Informatics & Computing, Indianapolis, IN, USA; Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Computer Science & Engineering, The University of Texas at Arlington, TX, USA; Genetics, Community & Family Medicine, Dartmouth Medical School, Lebanon, NH, USA
KG-SCCA funding source(s)
supported by the National Institutes of Health [R01 LM011360, U01 AG024904, RC2 AG036535, R01 AG19771, P30 AG10133] and the National Science Foundation [IIS-1117335] at IU; by the National Science Foundation [IIS-1117965, IIS- 1302675, IIS-1344152, DBI-1356628] at UTA; and by the National Institutes of Health [R01 LM011360, R01 LM009012, R01 LM010098] at Dartmouth.

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