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  "Title": "Network-Based Integration of Multi-Omics Data Using Sparse CCA",
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  "Description": "Provides an end-to-end workflow for integrative analysis\nof two omics layers using sparse canonical correlation analysis\n(sCCA), including sample alignment, feature selection, network\nedge construction, and visualization of gene-metabolite\nrelationships. The underlying methods are based on penalized\nmatrix decomposition and sparse CCA (Witten, Tibshirani and\nHastie (2009) <doi:10.1093/biostatistics/kxp008>), with design\nprinciples inspired by multivariate integrative frameworks such\nas mixOmics (Rohart et al. (2017)\n<doi:10.1371/journal.pcbi.1005752>).",
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      "title": "Align Multi-Omic Datasets",
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      "title": "Perform Sparse Canonical Correlation Analysis (sCCA)",
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      "title": "Example Multi-Omics Dataset",
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    {
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      "title": "Global Gene-Metabolite Correlation Heatmap",
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        "Load OmicNetR",
        "1. Generate example data",
        "2. Align samples",
        "3. Fit sparse CCA",
        "4. Convert loadings to an interaction network",
        "5. Visualize results",
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