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BioinformaticsBMC Bioinformatics
Peer-reviewed journal article

SmCCNet 2.0: A Comprehensive Tool for Multi-omics Network Inference

W. M. LiuiD, Thao VuiD, Iain R. KonigsbergiD, Katherine PratteiD, Yonghua ZhuangiD, Katerina J. KechrisiD

Abstract

SummarySparse multiple canonical correlation network analysis (SmCCNet) is a machine learning technique for integrating omics data along with a variable of interest (e.g., phenotype of complex disease), and reconstructing multi-omics networks that are specific to this variable. We present the second-generation SmCCNet (SmCCNet 2.0) that adeptly integrates single or multiple omics data types along with a quantitative or binary phenotype of interest. In addition, this new package offers a streamlined setup process that can be configured manually or automatically, ensuring a flexible and user-friendly experience. AvailabilityThis package is available in both CRAN: https://cran.r-project.org/web/packages/SmCCNet/index.html and Github: https://github.com/KechrisLab/SmCCNet under the MIT license. The network visualization tool is available at https://smccnet.shinyapps.io/smccnetnetwork/.

PDFDOICode

02 /Specification & Classification

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